WO2025178880A1 - Coiled tubing string mission profile, design, and optimization tool - Google Patents

Abstract

Systems and methods presented herein are configured to optimize the design and validation of coiled tubing strings. For example, a processing workflow may include generating a mission profile for a coiled tubing (CT) string for deployment in a well based on CT analytics. The processing workflow may also include creating a CT string design for the CT string based at least in part on a plurality of operational parameters of the well. The CT string design of the CT string defines a plurality of physical characteristics of the CT string. The processing workflow may further include adjusting one or more of the plurality of physical characteristics of the CT string design of the CT string based at least in part on the generated mission profile for the CT string and a predicted life cycle of the CT string.

Description

COILED TUBING STRING MISSION PROFILE, DESIGN, AND OPTIMIZATION TOOL

CROSS-REFERENCES TO RELATED APPLICATIONS

[0001] This application claims priority to and the benefit of U.S. Patent Application Serial No. 18/581,199, entitled “Coiled Tubing String Mission Profile, Design, and Optimization Tool,” filed February 19, 2024, and claims priority to and the benefit of U.S. Provisional Patent Application Serial No. 63/745,055, entitled “Coiled Tubing String Mission Profile, Design, and Optimization Tool,” filed January 14, 2025, both of which are hereby incorporated by reference in their entireties for all purposes.

BACKGROUND

[0002] The present disclosure generally relates to systems and methods for optimizing the design and validation of coiled tubing strings, also referred to as coiled tubing pipes.

[0003] This section is intended to introduce the reader to various aspects of art that may be related to various aspects of the present techniques, which are described and/or claimed below. This discussion is believed to be helpful in providing the reader with background information to facilitate a better understanding of the various aspects of the present disclosure. Accordingly, it should be understood that these statements are to be read in this light, and not as an admission of any kind.

[0004] In many well applications, coiled tubing is employed to facilitate performance of many types of downhole operations. Coiled tubing offers versatile technology due in part to its ability to pass through completion tubulars while conveying a wide array of tools downhole. A coiled tubing system may comprise many systems and components, including a coiled tubing reel, a coiled tubing pipe, an injector head, a gooseneck, lifting equipment (e.g., a mast or a crane), and other supporting equipment such as pumps, treating irons, or other components. Coiled tubing has been utilized for performing well treatment and/or well intervention operations in existing wellbores such as hydraulic fracturing operations, matrix acidizing operations, milling operations, perforating operations, coiled tubing drilling operations, and various other types of operations.

SUMMARY

[0005] A summary of certain embodiments described herein is set forth below. It should be understood that these aspects are presented merely to provide the reader with a brief summary of these certain embodiments and that these aspects are not intended to limit the scope of this disclosure.

[0006] Certain embodiments of the present disclosure include systems and methods for optimizing the design and validation of coiled tubing strings. For example, a processing workflow may include generating a mission profile for a coiled tubing (CT) string for deployment in a well based on CT analytics. The processing workflow may also include creating a CT string design for the CT string based at least in part on a plurality of operational parameters of the well. The CT string design of the CT string defines a plurality of physical characteristics of the CT string. The processing workflow may further include adjusting one or more of the plurality of physical characteristics of the CT string design of the CT string based at least in part on the generated mission profile for the CT string and a predicted life cycle of the CT string.

[0007] The mission profile describes the downhole and surface conditions that the CT string will see each time it is conveyed into and out of a well. The mission profile can include geometry and sizing of the surface equipment such as the CT reel and injector head gooseneck; fluids pumped from the surface through the CT string flowpath or through the CT string/tubing annular space; surface conditions such as the CT weight; downhole application; downhole conditions such as temperatures, pressures, annular velocities, tensile and compressive forces at the downhole end of the CT string; downhole fluids and environment such as H2S, fluids produced by the reservoir, and fluids already present in the well; wellbore geometry described by the hole survey; and wellbore geometry described by the completion tubulars.

[0008] Various refinements of the features noted above may be undertaken in relation to various aspects of the present disclosure. Further features may also be incorporated in these various aspects as well. These refinements and additional features may exist individually or in any combination. For instance, various features discussed below in relation to one or more of the illustrated embodiments may be incorporated into any of the above-described aspects of the present disclosure alone or in any combination. The brief summary presented above is intended to familiarize the reader with certain aspects and contexts of embodiments of the present disclosure without limitation to the claimed subject matter.

BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Various aspects of this disclosure may be better understood upon reading the following detailed description and upon reference to the drawings, in which:

[0010] FIG. 1 illustrates a schematic diagram of an example coiled tubing (CT) system, in accordance with embodiments of the present disclosure;

[0011] FIG. 2 illustrates a well analysis system including a CT design analysis system, in accordance with embodiments of the present disclosure; [0012] FIG. 3 illustrates a user interface showing functionality of a fatigue estimation engine of the CT design analysis system, in accordance with embodiments of the present disclosure;

[0013] FIGS. 4A through 4F illustrate various user interfaces of the CT design analysis system, in accordance with embodiments of the present disclosure;

[0014] FIG. 5 illustrates an example of a mission profile engine workflow based on manual inputs of total depth (TD) and circulating pressures, in accordance with embodiments of the present disclosure;

[0015] FIG. 6 illustrates an example of a mission profile engine workflow based on historical CT acquisitions (e.g., using CT analytics), in accordance with embodiments of the present disclosure;

[0016] FIG. 7 illustrates an example of a specific depth mission profile of a CT string based on historical CT acquisitions (e.g., using CT Analytics), in accordance with embodiments of the present disclosure;

[0017] FIG. 8 illustrates an example of a specific a mission profile for a single run based on historical CT acquisitions (e.g., using CT Analytics), where the mission profile can include wellhead pressure, circulating pressure, CT weight, and CT depth, in accordance with embodiments of the present disclosure;

[0018] FIG. 9 illustrates an example of a workflow for a CT String Design and Optimization Tool, in accordance with embodiments of the present disclosure;

[0019] FIG. 10 illustrates an optimization workflow utilizing the Mission Profile Generator and the CT String Design and Optimization Tool, in accordance with embodiments of the present disclosure; [0020] FIG. 11 illustrates a process of a continuous solution to a discretized design, in accordance with embodiments of the present disclosure;

[0021] FIG. 12 illustrates an example of a CT pipe profile as both (a) a continuous polynomial curve and (b) discretized wall thicknesses (WTs) of length l_mm or longer, in accordance with embodiments of the present disclosure;

[0022] FIG. 13 illustrates a forward process to create and evaluate a CT pipe design, in accordance with embodiments of the present disclosure;

[0023] FIG. 14 illustrates an example of a workflow for developing standardized CT string designs at a geographic level (e.g., with basin geography selected for the example), in accordance with embodiments of the present disclosure; and

[0024] FIG. 15 illustrates a method for implementing the techniques described herein, for example, using the CT design analysis system of FIG. 2, in accordance with embodiments of the present disclosure.

DETAILED DESCRIPTION

[0025] One or more specific embodiments of the present disclosure will be described below. These described embodiments are only examples of the presently disclosed techniques.

Additionally, in an effort to provide a concise description of these embodiments, all features of an actual implementation may not be described in the specification. It should be appreciated that in the development of any such actual implementation, as in any engineering or design project, numerous implementation-specific decisions must be made to achieve the developers’ specific goals, such as compliance with system-related and business-related constraints, which may vary from one implementation to another. Moreover, it should be appreciated that such a development effort might be complex and time consuming, but would nevertheless be a routine undertaking of design, fabrication, and manufacture for those of ordinary skill having the benefit of this disclosure.

[0026] When introducing elements of various embodiments of the present disclosure, the articles “a,” “an,” and “the” are intended to mean that there are one or more of the elements. The terms “comprising,” “including,” and “having” are intended to be inclusive and mean that there may be additional elements other than the listed elements. Additionally, it should be understood that references to “one embodiment” or “an embodiment” of the present disclosure are not intended to be interpreted as excluding the existence of additional embodiments that also incorporate the recited features.

[0027] As used herein, the terms “connect,” “connection,” “connected,” “in connection with,” and “connecting” are used to mean “in direct connection with” or “in connection with via one or more elements”; and the term “set” is used to mean “one element” or “more than one element.” Further, the terms “couple,” “coupling,” “coupled,” “coupled together,” and “coupled with” are used to mean “directly coupled together” or “coupled together via one or more elements.” As used herein, the terms “up” and “down,” “uphole” and “downhole”, “upper” and “lower,” “top” and “bottom,” and other like terms indicating relative positions to a given point or element are utilized to more clearly describe some elements. Commonly, these terms relate to a reference point as the surface from which drilling operations are initiated as being the top (e.g., uphole or upper) point and the total depth along the drilling axis being the lowest (e.g., downhole or lower) point, whether the well (e.g., wellbore, borehole) is vertical, horizontal or slanted relative to the surface. [0028] In addition, as used herein, the terms “real time”, ’’real-time”, or “substantially real time” may be used interchangeably and are intended to described operations (e.g., computing operations) that are performed without any human-perceivable interruption between operations.

For example, as used herein, data relating to the systems described herein may be collected, transmitted, and/or used in control computations in “substantially real time” such that data readings, data transfers, and/or data processing steps occur once every second, once every 0.1 second, once every 0.01 second, or even more frequent, during operations of the systems (e.g., while the systems are operating). In addition, as used herein, the terms “automatic” and “automated” are intended to describe operations that are performed or caused to be performed, for example, by a processing system (i.e., solely by the processing system, without human intervention). In addition, as used herein, the term “approximately equal to” may be used to mean values that are relatively close to each other (e.g., within 5%, within 2%, within 1%, within 0.5 %, or even closer, of each other).

[0029] Coiled tubing (CT) is used in the intervention of wells and is often selected as an intervention method for its capacity to pump fluids, its rigidity which delivers extended reach in deviated wells, its pulling and pushing capacity, and the ability to intervene in live wells, to name a few advantages. Design considerations for a CT string include yield strength (YS) of the metal, outer diameter (OD) of the CT, wall thickness(es) (WT) of the CT, lengths of the CT, Young’s modules, and so forth. The CT may be manufactured with segments that are welded together, where each segment may have different lengths and WT. A CT string with a single WT is known as “continuous”; whereas one with variations in WT is known as “tapered”. Operational requirements, wellbore and completion design, the mission profile, CT handling and logistics, and cost are all relevant inputs to the design of a CT string. As used herein, a “CT string” is intended to refer to the both a string of CT as well as the pipe used as part of the CT string.

[0030] In general, the fluid to be pumped in the CT and the required pump rates will determine circulating pressures. In addition, in general, the maximum anticipated circulating pressure will dictate the strength of the CT so as to avoid burst conditions. In addition, in general, reservoir pressures and the fluids in the well will determine the maximum anticipated wellhead pressure (MPWHP), which will also dictate the strength of the CT so as to avoid collapse conditions. In addition, if the CT will be used to carry solids to the surface (e.g., cuttings, sand cleanouts, and so forth), annular velocities of fluids in the CT/tubing and CT/casing annuli must be considered. These annular velocities are a function of the permissible flowrates inside the CT, and the radial clearance between the CT and the CT/tubing and CT/casing annuli. This radial clearance is a function of the CT OD. The chemistry of the downhole environment can also play an important role in the design of a CT string. For instance, softer metals are less susceptible to embrittlement than harder metals when exposed to sour environments (e.g., exposure to H2S, CO2, and so forth). Taking into account a degree of exposure to such sour environments will have an impact on YS selection.

[0031] The wellbore and completion is defined by the hole geometry and completion design. In turn, the hole geometry is defined by a hole survey, which provides a three-dimensional portrait of the well from the surface to its terminal or total depth (TD). A simple hole survey might be a perfectly vertical well, whereas more complicated hole surveys may introduce deviations, extended horizontal sections, doglegs, and tortuosity. These compounding hole survey features affect CT reach in the well. The completion design may be defined by the materials of the tubulars, the size of the tubulars, and the open hole region. The materials can have an impact on erosion between the tubular and the CT. The type of fluid produced from or pumped into the reservoir 16 can also have an impact on abrasion of tubular and pipes. For instance, operations in a dry gas well would see higher levels of abrasion. The CT string design may be adjusted to minimize the amount of abrasion generated during an operation (or a campaign of operations in wells if similar properties/environment).

[0032] As such, CT YS and WT sometimes selected to address erosion and abrasion risks for a given mission profile. The size of the tubulars may also impact the radial clearance between the CT and the internal diameter (ID) of the completions, and the radial clearance impacts CT reach. Materials and open hole regions also have an impact on expected frictions, which also impact CT reach. There are other design considerations such as net weight of the CT string as well as the size of the CT reel and/or whether it is on a vessel or on a platform. For example, certain locations have more restrictive weight requirements for transporting loads on highways. In addition, offshore platforms and vessels will have limited crane capacities. Furthermore, remote operations in the jungle may require the CT string to be hauled via helicopter with payload limitations. These weight limitations will have a direct impact on the design of the CT string. Finally, there is the consideration of cost. Cost can correlate with volume of raw material (e.g., longer or bigger WT), complexity of string geometry (e.g., tapered or additional telescoping sections), and manufacturing material and process (e.g., harder YS, quenching technologies).

[0033] There are several challenges associated with CT string design including, but not limited to, those described herein. First, conventional optimization techniques for CT string design are, at best, an educated guess with limited validation. For example, the CT string designer attempts to maximize reach, minimize risk of burst/collapse, maximize annular velocities for cleanouts, optimize weights for lifts/transport, maximize useful life, minimize manufacturing cost, and so forth). However, the CT string designer often does so in a toilsome manner that requires making an initial guess, manually running that design through different engines and simulators, and making adjustments based on outcomes. The embodiments described herein provide an automated, consistent optimization, based on both computation capabilities and leveraging experience of former CT string designs.

[0034] Second, wells are drilled in increasingly challenging environments (e g., due to depth, tortuosity, HPHT conditions, sour conditions, and so forth). The conventional optimization techniques for CT string design do not include a formal approach or process, and are lagging with respect to the evolution of well and intervention complexity. The embodiments described herein provide a baseline for optimizations that can be improved to address new challenges.

[0035] Third, the large variety of operational and wellbore considerations leads to a large variety in CT string designs. For example, in a single calendar year, an oil and gas operator may order several hundreds of unique varieties of CT strings. There has heretofore been no attempt to standardize CT string designs across different locations, geographical areas, basins, or CT application or job types. Such an exercise of standardizing strings could produce fewer varieties of CT strings that could still meet the operational requirements worldwide. The embodiments described herein leverage CT acquisition data from around the world to generate mission profdes that can be used to generate standardized (or default) CT string designs for specific downhole and operating conditions.

[0036] With the foregoing in mind, FIG. 1 illustrates a schematic diagram of an example CT system 10. As illustrated, in certain embodiments, a CT string 12 may be run into a wellbore 14 that traverses a hydrocarbon-bearing formation 16 (i.e., reservoir). While certain elements of the CT system 10 are illustrated in FIG. 1, other elements of the CT system 10 (e.g., blow-out preventers, wellhead “tree”, etc.) may be omitted for clarity of illustration. In certain embodiments, the CT system 10 includes an interconnection of pipes, including vertical and/or horizontal casings 18, CT 20, and so forth, that connect to a surface facility 22 at the surface 24 of the CT system 10. In certain embodiments, the CT 20 extends inside the casing 18 and terminates at a tubing head (not shown) at or near the surface 24. In addition, in certain embodiments, the casing 18 contacts the wellbore 14 and terminates at a casing head (not shown) at or near the surface 24. It should be appreciated that the embodiments described herein may be applicable to oil and gas wells as well as other types of wells including, but not limited to, geothermal or carbon capture, utilization, and storage (CCUS) wells, for example.

[0037] In certain embodiments, a bottom hole assembly (“BHA”) 26 may be run inside the casing 18 by the CT 20. As illustrated in FIG. 1, in certain embodiments, the BHA 26 may include a downhole motor 28 that operates to rotate a drill or mill bit 30 (e.g., during drilling or milling operations) or other downhole tools. In certain embodiments, the downhole motor 28 may be driven by hydraulic forces carried in fluid supplied from the surface 24 of the CT system 10. In certain embodiments, the BHA 26 may be connected to the CT 20, which is used to run the BHA 26 to a desired location within the wellbore 14. It is also contemplated that, in certain embodiments, the rotary motion of the drill bit 30 may be driven by rotation of the CT 20 effectuated by a rotary table or other surface-located rotary actuator. In such embodiments, the downhole motor 28 may be omitted.

[0038] In certain embodiments, the CT 20 may also be used to deliver fluid 32 to the drill bit 30 through an interior of the CT 20 to aid in the drilling process and carry cuttings and possibly other fluid or solid components in return fluid 34 that flows up the annulus between the CT 20 and the casing 18 (or via a return flow path provided by the CT 20, in certain embodiments) for return to the surface facility 22. It is also contemplated that the return fluid 34 may include remnant proppant (e.g., sand) or possibly rock fragments that result from a hydraulic fracturing application, and flow within the CT system 10. Under certain conditions, fracturing fluid and possibly hydrocarbons (oil and/or gas), proppants and possibly rock fragments may flow from the fractured formation 16 through perforations in a newly opened interval and back to the surface 24 of the CT system 10 as part of the return fluid 34. In certain embodiments, the BHA 26 may be supplemented behind the rotary drill by an isolation device such as, for example, an inflatable packer that may be activated to isolate the zone below or above it and enable local pressure tests. In addition, in certain embodiments, the BHA 26 may include a tractor system that is capable of improving reach and WOB of the BHA 26 during CT operations.

[0039] As such, in certain embodiments, the CT system 10 may include a downhole well tool 36 that is moved along the wellbore 14 via the CT 20. In certain embodiments, the downhole well tool 36 may include a variety of drilling/cutting tools coupled with the CT 20. In the illustrated embodiment, the downhole well tool 36 includes the drill bit 30, which may be powered by the downhole motor 28 (e.g., a positive displacement motor (PDM), or other hydraulic motor) of the BHA 26. In certain embodiments, the wellbore 14 may be an openhole wellbore or a cased wellbore defined by the casing 18. In addition, in certain embodiments, the wellbore 14 may be vertical or horizontal or inclined. It should be noted the downhole well tool 36 may be part of various types of BHAs 26 coupled to the CT 20.

[0040] As also illustrated in FIG. 1, in certain embodiments, the CT system 10 may include a downhole sensor package 38 having multiple downhole sensors 40. In certain embodiments, the sensor package 38 may be mounted along the CT string 12, although certain downhole sensors 40 may be positioned at other downhole locations in other embodiments. In addition, in certain embodiments, downhole sensors 40 disposed on the CT 20 may be configured to detect downhole flow rates, downhole temperatures, and downhole pressures, and so forth, in the wellbore 14. In addition, in certain embodiments, downhole sensors 40 disposed on the casing 18 may be configured to detect downhole temperatures, downhole pressures, axial load (or “weight”) and torque applied on the bit, casing collar locators (CCLs), resistivity, and so forth, in the wellbore 14.

[0041] In certain embodiments, data from the downhole sensors 40 may be relayed uphole to a CT design analysis system 42 (e.g., a computer-based processing system) disposed at the surface 24 and/or other suitable location of the CT system 10. In certain embodiments, the data may be relayed uphole in substantially real time (e g., relayed while it is detected by the downhole sensors 40 during operation of the downhole well tool 36) via a wired or wireless telemetric control line 44, and this real-time data may be referred to as edge data. In certain embodiments, the telemetric control line 44 may be in the form of an electrical line, fiber-optic line, or other suitable control line for transmitting data signals. In certain embodiments, the telemetric control line 44 may be routed along an interior of the CT 20, within a wall of the CT 20, or along an exterior of the CT 20. In addition, as described in greater detail herein, additional data (e.g., surface data) may be supplied by surface sensors 46 and/or stored in a memory location 48. By way of example, historical data and other useful data may be stored in the memory location 48 such as a cloud storage 50.

[0042] As illustrated, in certain embodiments, the CT 20 may be deployed by a CT unit 52 and delivered downhole via an injector head 54. In certain embodiments, the injector head 54 may be controlled to slack off or pick up the CT 20 so as to control the tubing string weight and, thus, the weight-on-bit (WOB) acting on the drill bit 30 (or the downhole well tool 36). In certain embodiments, the downhole well tool 36 may be moved along the wellbore 14 via the CT 20 under control of the injector head 54 so as to apply a desired tubing weight and, thus, to achieve a desired rate of penetration (ROP) as the drill bit 30 is operated. Depending on the specifics of a given application, various types of data may be collected downhole, and transmitted to the CT design analysis system 42 in substantially real time to facilitate improved operation of the downhole well tool 36. For example, as described in greater detail herein, the data may be used to fully or partially automate downhole operations, to optimize the downhole operations, and/or to provide more accurate predictions regarding components or aspects of the downhole operations.

[0043] In certain embodiments, fluid 32 may be delivered downhole under pressure from a pump unit 56. In certain embodiments, the fluid 32 may be delivered by the pump unit 56 through the downhole motor 28 to power the downhole motor 28 and, thus, the drill bit 30. In certain embodiments, the return fluid 34 is returned uphole, and this flow back of the return fluid 34 is controlled by suitable flowback equipment 58. In certain embodiments, the flowback equipment 58 may include chokes and other components/ equipment used to control flow back of the return fluid 34 in a variety of applications, including well treatment applications.

[0044] As described in greater detail herein, the CT unit 52, the injector head 54, the pump unit 56, and the flowback equipment 58 may include advanced surface sensors 46, actuators, and local controllers, such as PLCs, which may cooperate together to provide sensor data to receive control signals from, and generate local control signals based on communications with, respectively, the CT design analysis system 42. In certain embodiments, as described in greater detail herein, the surface sensors 46 may include flow rate, pressure, and fluid rheology sensors 46, among other types of sensors. In addition, as described in greater detail herein, the actuators may include actuators for pump and choke control of the pump unit 56 and the flowback equipment 58, respectively, among other types of actuators.

[0045] In certain embodiments, surface sensors 46 of the CT unit 52 may be configured to detect positions of the CT 20, weights of the CT 20, and so forth. In addition, in certain embodiments, surface sensors 46 of the injector head 54 may be configured to detect wellhead pressure, and so forth. In addition, in certain embodiments, surface sensors 46 of the pump unit 56 may be configured to detect pump pressures, pump flow rates, and so forth. In addition, in certain embodiments, surface sensors 46 of the flowback equipment 58 may be configured to detect fluids production rates, solids production rates, and so forth.

[0046] FIG. 2 illustrates a well analysis system 60 that may include the CT design analysis system 42 to facilitate the optimization of design of CT strings 12, as described in greater detail herein. In certain embodiments, the CT design analysis system 42 may include one or more analysis modules 62 (e.g., a program of computer-executable instructions and associated data) that may be configured to perform various functions of the embodiments described herein. In certain embodiments, to perform these various functions, the one or more analysis modules 62 may execute on one or more processors 64 of the CT design analysis system 42, which may be connected to one or more storage media 66 of the CT design analysis system 42. Indeed, in certain embodiments, the one or more analysis modules 62 may be stored in the one or more storage media 66.

[0047] In certain embodiments, the computer-executable instructions of the one or more analysis modules 62, when executed by the one or more processors 64, may cause the one or more processors 64 to generate one or more models, which may be used by the CT design analysis system 42 to optimize the design of CT strings 12, as described in greater detail herein.

In certain embodiments, the analysis modules 62 that enable the embodiments described herein may run locally (e.g., on a local computer), as a cloud-based solution, or as a plugin to existing software.

[0048] In certain embodiments, the one or more processors 64 may include a microprocessor, a microcontroller, a processor module or subsystem, a programmable integrated circuit, a programmable gate array, a digital signal processor (DSP), or another control or computing device. In certain embodiments, the one or more processors 64 may include machine learning and/or artificial intelligence (Al) based processors. In certain embodiments, the one or more storage media 66 may be implemented as one or more non-transitory computer-readable or machine-readable storage media. In certain embodiments, the one or more storage media 66 may include one or more different forms of memory including semiconductor memory devices such as dynamic or static random access memories (DRAMs or SRAMs), erasable and programmable read-only memories (EPROMs), electrically erasable and programmable read-only memories (EEPROMs) and flash memories; magnetic disks such as fixed, floppy and removable disks; other magnetic media including tape; optical media such as compact disks (CDs) or digital video disks (DVDs); or other types of storage devices. Note that the computer-executable instructions and associated data of the analysis module(s) 62 may be provided on one computer-readable or machine-readable storage medium of the storage media 66, or alternatively, may be provided on multiple computer-readable or machine-readable storage media distributed in a large system having possibly plural nodes. Such computer-readable or machine-readable storage medium or media are considered to be part of an article (or article of manufacture), which may refer to any manufactured single component or multiple components. In certain embodiments, the one or more storage media 66 may be located either in the machine running the machine-readable instructions, or may be located at a remote site from which machine-readable instructions may be downloaded over a network for execution.

[0049] In certain embodiments, the processor(s) 64 may be connected to a network interface 68 of the CT design analysis system 42 to allow the CT design analysis system 42 to communicate with multiple downhole sensors 40 and surface sensors 46 described herein, as well as communicate with the actuators 70 and/or PLCs 72 of surface equipment 74 (e.g., CT units 52, injector heads 54, pump units 56, flowback equipment 58, and so forth) and of downhole equipment 76 (e.g., BHAs 26, downhole motors 28, drill bits 30, downhole well tools 36, and so forth) of various CT systems 10 for the purpose of optimizing the design process for CT strings 12 of CT systems 10, as described in greater detail herein. In certain embodiments, the network interface 68 may also facilitate the CT design analysis system 42 to communicate data to the cloud storage 50 (or other wired and/or wireless communication network) to, for example, archive the data and/or to enable external computing systems 78 to access the data and/or to remotely interact with the CT design analysis system 42.

[0050] It should be appreciated that the well analysis system 60 illustrated in FIG. 2 is only one example of a well analysis system, and that the well analysis system 60 may have more or fewer components than shown, may combine additional components not depicted in the embodiment of FIG. 2, and/or the well analysis system 60 may have a different configuration or arrangement of the components depicted in FIG. 2. In addition, the various components illustrated in FIG. 2 may be implemented in hardware, software, or a combination of both hardware and software, including one or more signal processing and/or application specific integrated circuits. Furthermore, the operations of the well analysis system 60 as described herein may be implemented by running one or more functional modules in an information processing apparatus such as application specific chips, such as application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), programmable logic devices (PLDs), systems on a chip (SOCs), or other appropriate devices. These modules, combinations of these modules, and/or their combination with hardware are all included within the scope of the embodiments described herein.

[0051] As described in greater detail herein, the embodiments described herein facilitate the design of CT strings 12. For example, a variety of data (e.g., downhole data and surface data) may be collected to enable optimization of the design of the CT strings 12 illustrated in FIG. 1 by the CT design analysis system 42 illustrated in FIG. 2 (or other suitable processing systems). In particular, the embodiments described herein include two software engines that enable new workflows:

1. Mission Profile Generator: Provides a CT intervention mission profile with which to evaluate the performance of a CT string design.

2. CT String Design and Optimization Tool: Designs and optimizes a CT string design based on user-defined requirements and mission profile.

[0052] FIG. 3 illustrates a user interface 80 of the CT design analysis system 42 that partially fulfills the functionality of the Mission Profile Generator as a fatigue estimation engine. A user may provide a constant pressure 82 (e.g., circulating pressure inside a CT string 12) and an arch radius 84 (e.g., radius of a gooseneck of an associated injector head 54) and the fatigue estimation engine outputs machine cycles 86 and number of trips to failure 88. Elements that are missing from the illustrated estimator are expected behaviors such as pull tests, the impact of the fatigue induced by the plastic deformation of spooling and unspooling the CT 20 from the work reel or drum of the CT unit 52, and modifying factors.

[0053] FIGS. 4A through 4F illustrate various user interfaces 90, 98, 104, 108, 112, 116 of the CT design analysis system 42 that partially fulfills the functionality of the CT String Design and Optimization Tool. However, it is noted that one or more engines, simulations, or models are used by an engineer to design a CT string 12 and validate that the designed CT string 12 will meet operational requirements. FIGS. 4A through 4F illustrate one example of how an engineer may design a CT string 12, but it should be appreciated that there are many other approaches, order of operations, and considerations that are not captured by this example.

[0054] FIG. 4A illustrates a first user interface 90 through which an engineer may choose CT string material 92, OD 94, thickness 96, length, and geometry. FIG. 4B illustrates a second user interface 98 (showing two different tabs being selected) through which an engineer may define hole survey data 100 and tubular data 102. FIG. 4C illustrates a third user interface 104 through which an engineer may load data for a CT design (e.g., as illustrated by element 106). FIG. 4D illustrates a fourth user interface 108 through which an engineer may verify reach 110 (e.g., maximum tool depth) of a CT string 12 with a tubing forces module (TFM). FIG. 4E illustrates a fifth user interface 112 through which an engineer may modify the CT string design to get the required reach and desired WOB 114 and torque-on-bit (TOB) margins. FIG. 4F illustrates a sixth user interface 116 illustrating a plot 118 from which an engineer may validate safety margins of effective forces and differential pressures based on the worst-case scenario and operating limit. After entering all of the data via the user interfaces 90, 98, 104, 108, 112, 116, an engineer may validate a number of runs or cycles to failure using the fatigue estimation engine that is used in conjunction with the user interface 80 illustrated in FIG. 3. [0055] The embodiments of the present disclosure extend the general workflows that are facilitated by the user interfaces 80, 90, 98, 104, 108, 112, 116 of the CT design analysis system 42 illustrated in FIGS. 3 through 4F via additional functionality of the Mission Profile Generator and the CT String Design and Optimization Tool described in greater detail herein.

Mission Profile Generator

[0056] The Mission Profile Generator is an engine that generates a mission profile for a design of a CT string 12. Much like a hypothetical racetrack or landscape against which a car’s mileage and performance can be measured against, a CT string mission profile can be used to evaluate and validate the performance of a CT string 12. FIG. 3 illustrates basic functionality of a CT performance engine that outputs cycles 86 to failure as a function of arch radius 84 and circulating pressure 82. However, the user interface 80 illustrated in FIG. 3 does not accurately capture how CT 20 is cycled throughout its life. Rather, it assumes cycling the full length of the CT 20 and back. It also does not allow for a more nuanced circulating pressure profile, rather assuming a static pressure.

[0057] The embodiments of the present disclosure include a Mission Profile Generator engine that provides a time-gated mission profile for depth and pressure cycling, thereby more accurately capturing variations in these parameters. FIG. 5 illustrates a workflow 120 of this engine, where an engineer manually provides inputs 122 (e.g., design requirements) such as TD, circulating pressure range, and pull test frequency and range. By extension, the engineer could manually provide inputs such as CT depth and pump rate to automatically simulate the anticipated circulating pressure range and annular velocities, among other mission profile inputs. Likewise, the engineer could leverage TFM to simulate anticipated CT weights as an input for the mission profile. The engine 124 would then generate a time-gated mission profile of depth and pressures as a final deliverable 126. It is noted that, in the figures described herein, certain shaded blocks (e.g., blocks 124, 126, 132, 144, 148, 154, 158, 176, and 226) designate that the processing steps are at least partially performed automatically (e.g., without human intervention) by the analysis module(s) 62 (e.g., executed by a CT design analysis system 42) described in greater detail herein.

[0058] If the engineer wants to leverage existing job acquisitions, they may use the Mission Profile Generator as per the workflow 128 illustrated in FIG. 6. In this example, the Mission Profile Generator may be provided with inputs 130 such as one or more locations, geological locations (e.g., GeoUnits), basins, and/or job types. In certain embodiments, one or more historical CT strings 12 could be selected. Or the mission profile could be limited to a specific campaign or field. The engine 128 would then generate a mission profile based on CT analytics as a final deliverable 126.

[0059] FIG. 7 illustrates an example of a specific CT depth mission profile 134 for a particular CT string 12. This specific CT string 12 could be used to evaluate the performance of a new CT string design using actual RIH/POOH cycling, including pull tests, as well as circulating pressures during each job. In addition to CT depth, FIG. 8 provides examples of mission profiles of wellhead pressure 136, circulating pressure 138, and CT weight 140.

[0060] In each of these examples, the Mission Profile Generator may directly use historical data, or it may derive a new mission profile that is the average or worst-case of mission profiles that are filtered using geography, field, job type, and so forth.

CT String Design and Optimization Tool

[0061] The CT String Design and Optimization Tool is an engine (or multiple engines that work jointly) that outputs a CT string design based on user inputs (e.g., operational requirements) and optimizes these based on requirements and key performance indicators (KPIs).

FIG. 9 illustrates an example workflow 142 of the CT String Design and Optimization Tool. It is noted that the majority of the processing performed in the workflow 142 of FIG. 9 are at least partially performed automatically (e.g., without human intervention) by the analysis module(s) 62 (e.g., executed by a CT design analysis system 42) described in greater detail herein.

[0062] In a first stage 144 of the workflow 142 (e.g., Collect Requirements 146 and Generate Mission Profile 148), a user may provide operational requirements 150 that include, for example, environment (e.g., land, offshore platform, vessel, and so forth, whether fixed or moving), hole survey, TD, MPWHP, maximum reservoir pressure (as well as maximum temperature of the well), maximum WOB/TOB, and so forth. In addition, other types of operational parameters 150 that may impact the MP 156 may include, but are not limited to, the types of downhole well tools 36 that are used in the CT system 10 (e.g., the BHA selection including tractors, agitators, j ars, fishing tools, hydraulically activated tools, perforating guns, and so forth). Other requirements at this stage 144 may include logistic requirements 152 (e.g., weight and size limitation for the purposes of transporting or carrying or installing the string) and cost limitations 154. In certain embodiments, the Mission Profile Generator may also be used to guide or complete the operational requirements 150; for instance, CT analytics may be used to find worst-case hole survey, TD, MPWHP, WOB/TOB for a given geography, environmentjob type, and so forth to output a mission profile (MP) 156.

[0063] In addition, in certain embodiments, the workflow 142 may include augmenting the mission profile from a single well to multiple wells such that the CT pipe may be optimized against the augmented mission profile. The augmented mission profile may be called a “Campaign”. In certain embodiments, the campaign mission profile may be defined based on multiple different wells, or as permutations and modulations from one single well. In addition, in certain embodiments, to create permutations and modulations from a single well, the campaign mission profile may use sensitivity analysis to modulate any parameter that defines the well, as described in greater detail herein. In certain embodiments, the campaign may include a combination of existing wells and permutations and modulations of one or more wells. In other words, in certain embodiments, all of the functionality of the workflow 142 illustrated in FIG. 9 may be extended to a campaign having multiple wells.

[0064] A second stage of the workflow 142 (e.g., Design a CT string 158) designs an initial CT string 12 by fixing YS, OD, WT, and length of individual sections. It does so by pursuing an initial “guess” (e.g., of YS in block 160 and OD, WT, and length in block 162) that can be based on historical designs, best practices, logic, randomized, and manual user-defined inputs. The initial “guess” is then subjected to the TFM 164 to confirm proper reach, WOB, and TOB, among other parameters, at TD. A determination of whether sufficient margins in terms of burst and collapse conditions are confirmed. In addition, a decision may be made as to whether the reach is acceptable (decision block 166). If the reach is not acceptable, the WT and section lengths can be adjusted (e.g., block 168) to change the string’s geometry and achieve desired reach and pressure performance (e.g., by proceeding back to block 162). YS and OD can be used to modify reach and pressure performance. These design choices impact net weight, which can impact compliance with logistic limits 170. Material choice, WT(s), and geometry can also impact cost. In addition, a decision may be made as to whether the weight is acceptable (decision block 172). If the weight is not acceptable, the WT and section lengths can be adjusted (e.g., block 168) to change the string’s geometry and achieve desired reach and pressure performance (e.g., by proceeding back to block 162). However, if the weight is acceptable, the CT string design 174 may be output. The user can define desired objectives and weight of those objectives (e.g., prioritize maximizing WOB or prioritize minimizing the net weight). The adjustments of the second stage can be automated to repeatedly iterate on a CT string design 174 in an automatic fashion, delivering a CT string design 174 in seconds or a fraction of a second. In addition, in certain embodiments, creating the CT string design 174 may include confirming cost limits, weight-on-bit limits, pull-on-bit limits, and maximum yield stress limits with the CT string design 174.

[0065] A third stage (e.g., the Optimize CT String based on a CT string fatigue engine and Cost block 176) takes the CT string design 174 provided by the second stage 158 and subjects it to the MP 156 provided by the first stage 144 using a CT life prediction model (CTLPM) (e.g., a CT pipe fatigue model). The third stage 176 performs fine-tuning of the existing design to maximize fatigue life. The third stage 176 may also perform fine-tuning to minimize net weight and cost. In effect, the third stage 176 is an optimization stage that may, in certain embodiments, be incorporated into the second stage 158 depending on back-end implementation and optimization methodology.

[0066] As illustrated in FIG. 9, in certain embodiments, the third stage 176 may include running the CT string design 174 in the MP 156 to 100% CT string fatigue profile (block 178). Then, various KPIs may be calculated (block 180) and a determination may be made as to whether the calculated KPIs are acceptable (decision block 182). If the calculated KPIs are acceptable, the optimized CT string design 174 may be the final deliverable 184. However, if the calculated KPIs are not acceptable, the CT string design 174 may be further optimized based on the CT string fatigue profile (block 186) and a reconfirmation that reach and logistics limits are met may be made (188) before proceeding back to block 178. [0067] A solution was developed to fulfill the goal presented in block 158 of FIG. 9. In particular, given a particular MP 156 (i.e., hole survey, completion, tubing forces), the proposed algorithm provides an optimized geometry of the CT string 12. First, an initial CT string design of a given OD, length, and material is proposed. Then, the geometry (i.e., the wall thickness along the CT string 12) will be changed iteratively to optimize on the following properties: maximum depth, maximum pull, maximum WOB, YS, total weight of the string. Other implementations may fix other parameters (e.g., wall thickness) and sensitize to optimize over the rest of the parameters (e.g., OD, material, length). Other implementations may also optimize for KPIs such as minimizing circulating pressure for an operating envelope of flow rates and fluids, annular velocity for a given completion geometry, and even cost.

[0068] FIG. 10 illustrates an optimization workflow 190 utilizing the Mission Profile Generator and the CT String Design and Optimization Tool, as described in greater detail herein. As illustrated in FIG. 10, the optimization workflow 190 may include cyclic steps where a TFM 164 acts on a CT string design 174 (block 192) to determine variables of interest, for which an objective function is defined (block 194), the value of which is optimized by an Optimizer (block 196) to generate data points that may be interpolated (block 198) to create a continuous curve that may be discretized to create a JavaScript Object Notation (JSON) (block 200), which may be used to update the CT string design 174.

[0069] The embodiments described herein alter a continuous design of a CT string 12 before discretizing it into a specific CT string design 174 that can be manufactured. FIG. 11 illustrates a process of a continuous solution (e.g., the continuous curves on the left) to a discretized design (e.g., the discretized string design on the right). It is noted that the discretized values on the right are based on the existing wall thicknesses that CT pipe suppliers are capable of manufacturing. Therefore, this step is indispensable to producing an actually manufacturable CT pipe. The string design may be tested through the TFM 164 to compute the various KPIs mentioned earlier. These KPIs may then be combined into an objective function to obtain a score that evaluates the general performance of a CT string design 174 and helps comparing two different CT string designs 174. In addition to TFM, other models can be used to calculate KPIs for the string design.

[0070] In certain embodiments, an objective function may be defined as per Eq. (1):

[0071] where r is the reach, s is the maximum YS, w is the maximum WOB, p is the maximum pressure-on-bit (POB), m is the net weight of the CT pipe, and _r, t_s, T_W, T_p are the target reach, target maximum YS, target WOB, and target POB, respectively. The objective function is designed to take into account all of the forementioned variables to guide the optimizer towards an efficient design (i.e., with maximum capacities regarding these variables).

[0072] In addition, in certain embodiments, an objective function that adds weightings to the objective function defined in Eq. (1) is presented as Eq. (2):

[0073] where a is a parameter proportional to the importance of the net CT pipe weight, y is a parameter proportional to the importance of the WOB, and P is a parameter proportional to the importance of the POB. These specific functions, or any similar equation including additional parameters, help the user to give more importance to some KPIs in particular while neglecting some others.

[0074] In certain embodiments, an interpolating curve may be used to create a CT pipe profile based on wall thicknesses from end-to-end, and a discretization method may be used that takes that interpolating curve and turns it into discrete segments based on manufacturable wall thicknesses (this being based on the wall thicknesses that manufacturers typically allow) and the smallest strip of CT material that must be used before a wall thickness may change. FIG. 12 illustrates an example of a CT pipe profile as both (a) a continuous polynomial curve and (b) discretized wall thicknesses (WTs) of length l_min or longer. The number of possible values for the ID and up to n_section = [— ^ — ] number of sections for a given CT pipe of length L with *-min minimum CT length for WT transition may be determined.

[0075] Thus, the embodiments described herein may include such interpolation, a discretization process, integration of one or more physics models, and an objective function in a schema that comprises a forward pass and loopback pass. The optimization schema may include two stages. The first stage is known as the forward pass 202 and is an iteration during which a CT pipe design may be generated (block 204), discretized (block 206), simulated using a CTF model (block 208), and evaluated based on the objective function (block 210). The second stage is the loopback pass which implements the optimization algorithm that helps search for an optimal solution. FIG. 13 illustrates such forward pass 202 to evaluate a design, given a set of WTs, X_w = a mission profile P, and a mapping /), such that:

/p(^w) ⁼ y_w (3) where yw is the value of the objective function obtained from a pipe design defined using an interpolation method [0076] In certain embodiments, the optimizer may be benchmarked against an ideal or perfectly scoring CT pipe design. For example, in certain embodiments, a method and metric to quantify the degree of match between the optimizer’s output and an analytic solution for well- posed wells for which analytic solutions exist may be developed based on numerical methods or otherwise. Such a metric could be used to evaluate if changes to the optimizer are improving or deteriorating the optimizer’s performance given that, ideally, the optimizer should strive to match the analytic solution exactly. In certain embodiments, a library of different theoretical wells with varying depths and numerical solutions for CT pipes of every possible OD and material property may be used. In addition, in certain embodiments, a holistic benchmark that is foundational in regression testing for the CT pipe design optimizer may be used.

[0077] In certain embodiments, the output solution may be manually fine-tuned. For example, the optimizer may provide a CT pipe designer with the ability to override and fine-tune sections of the optimized pipe. Certain embodiments of this fine-tuning could be performed with virtual dials or knobs (e.g., presented via the CT design analysis system 42 illustrated in FIG. 2). In addition, a user may modulate and/or fine-tune the CT pipe’s solution before, during, or after the optimizer has converged on a solution.

[0078] In certain embodiments, other models may be included and incorporate modelspecific KPIs in the objective function to broaden design features. For example, CT hydraulics models, fluid models, and fluid libraries may be included to optimize the CT pipe designs based on hydraulic and fluid performance. In addition, KPIs may be included related to hydraulic and fluid performance including, but not limited to, burst and collapse pressures, maximum allowable flow rates for a given fluid, annular velocities, and carrying capacity. Thess KPIs (e.g., annular velocities and carrying capacity) are particularly interesting because they go beyond addressing the performance of the CT pipe and start optimizing it for service-specific applications such as sand cleanouts or milling. To accomplish this, certain embodiments may include using steady state models such as annular velocity calculations, carrying capacity models, and other design aid modules. In certain embodiments, a CT pressure and tension limit model (e.g., a CT operating envelope model) may be included to calculate the worst-case operating point during an operation. In addition, certain embodiments may include a KPI that provides a metric of how close the CT pipe design is to its operating limit based on the output from the CT pressure and tension limit model, and optimization may be performed based on that KPI.

[0079] In certain embodiments, the CT pipe design optimizer’s loopback pass may utilize domain-agnostic methods to search for a solution. Future versions of the optimizer may leverage and trade-off two additional methods to inform and improve the loopback process. First, historical data may be used to continuously train and improve the optimization algorithm.

Second, physics-based logic may be implemented that will bound and improve how the optimizer searches for a solution. These approaches, though far from trivial in their implementation, are expected to improve the optimizer’s initial guess and the effectiveness of its search vector by avoiding iterations that are unlikely to converge on a valuable solution.

[0080] The CT String Design and Optimization Tool described herein may be used in a workflow, the purpose of which is to create one or more standardized CT string designs 174 that will meet the operational requirements of a constrained geography and/or job type. For example, consider the geography of a basin that includes several countries. These countries, historically, might be purchasing 20+ unique varieties of CT strings 12 each year. The workflow could design standardized CT strings 12 that meet the operational requirements of all the countries in that basin. Instead of 20+ unique varieties, the workflow may find that five standardized designs could meet all the operational requirements for the basin. In addition, the workflow may use the KPIs of the CT string Design and Optimization Tool to compare the standardized designs against the 20+ CT strings 12 that have been historically used in the basin; this would require using the basin’s mission profile. The standardized designs could also be validated by input from the technical experts and domains in the basin. The standardized designs could also be used to secure better pricing in the procurement of future CT strings 12.

[0081] FIG. 14 illustrates an example of a workflow 212 for developing standardized CT string designs at a geographic level (e.g., with basin geography selected for the example). For example, the workflow 212 may begin with Collect Requirements 214 (e.g., Cluster Locations by CT OD Size 216, Cluster Locations by TD 218, and Collect Worst-Case for each Cluster Location 220), which may be used as inputs to Collect Strings for Comparison 222 (e.g., including to Collect historical CT string designs 174 for each cluster) and, for each clustered CT OD and basin, incorporating the processing steps 144, 158, 176 of the workflow 142 described above with reference to FIG. 9. In addition, for each clustered CT OD and basin, the CT string data collected in block 222 may be used to Compute KPIs for historical CT string designs 174 (block 226), which are collected in block 224.

[0082] From there, an Initial Deliverable 228 may include a proposed CT string design 174 (e.g., per CT OD and basin cluster) from the workflow 142 and the computed KPIs for the proposed CT string design 174. Then, a Cost Estimate 230 for the proposed CT string design 174 may be performed based on historical CT string designs 174. In addition, the proposed CT string design 174 may be validated with technical experts and domains who may share standardized CT strings with their respective basin (block 232), which may be requested based on local job designs. Then, a Final Deliverable 234 may include a finalized CT string by basin, a forecast of orders of CT strings per year, and a review of quotes from CT pipe manufacturers.

[0083] Although certain shaded blocks (e.g., blocks 124, 126, 132, 144, 148, 154, 158, 176, and 226) in the figures illustrating the various workflows described herein are intended to designate processing steps that may be at least partially automated (e.g., by utilizing the analysis module(s) 62, for example, executed by a CT design analysis system 42, as described in greater detail herein), some of the other blocks may also be at least partially automated to further optimize the design of CT strings 12. For example, in certain embodiments, the Cost Estimate 230 functionality may also be performed automatically.

[0084] FIG. 15 illustrates a method 236 for implementing the techniques described herein, for example, using the CT design analysis system 42. As illustrated, in certain embodiments, the method 236 may include generating a mission profile for a CT string 12 for deployment in a well based on CT analytics (block 238). In addition, in certain embodiments, the method 236 may include creating a CT string design 174 for the CT string 12 based at least in part on a plurality of operational parameters of the well, wherein the CT string design 174 of the CT string 12 defines a plurality of physical characteristics of the CT string design 174 (block 240). In addition, in certain embodiments, the method 236 may include adjusting one or more of the plurality of physical characteristics of the CT string design 174 of the CT string 12 based at least in part on the generated mission profile for the CT string 12 and a predicted life cycle of the CT string 12 (block 242). In addition, in certain embodiments, the method 236 may include performing blocks 238, 240, and 242 for each of a plurality of combinations of cluster locations, basin identifications, and CT outer diameter size of other CT string designs 174 having similar cluster locations and basin identifications as the well, and having a similar CT outer diameter as the CT string design 174.

[0085] In certain embodiments, the mission profile for the CT string 12 may be generated based at least in part on a location and environment of the well, a basin of the well, or some combination thereof. In addition, in certain embodiments, the plurality of operational parameters of the well may include a hole survey for the well, a total depth of the well, a maximum anticipated wellhead pressure of the well, a maximum reservoir pressure of the well, a maximum temperature of the well, a maximum weight-on-bit of the well, a maximum torque-on-bit of the well, a maximum pump rate of the well, a type of one or more fluids pumped into the well, a minimum annular velocity of the well, a degree to which the well operates in a sour environment, physical characteristics of casings of the well, whether the well is an offshore well or an onshore well, whether the CT is deployed from a fixed platform or a moving vessel, a type of one or more downhole well tools used, or some combination thereof.

[0086] In addition, in certain embodiments, the method 236 may include augmenting the mission profile for the CT string 12 of a single well for multiple different wells such that CT pipe of the CT string 12 is optimized against the augmented mission profile. In such embodiments, the augmented mission profile may be defined based on the multiple different wells or as permutations and modulations of the single well. In addition, in such embodiments, the augmented mission profile may utilize sensitivity analysis to modulate one or more of the plurality of operational parameters of the well.

[0087] In addition, in certain embodiments, the plurality of physical characteristics of the CT string 12 may include a yield strength of metal of the CT string 12, an outer diameter of the CT string 12, a wall thickness of the CT string 12, a length of the CT string 12, or some combination thereof. In addition, in certain embodiments, the plurality of physical characteristics of the CT string 12 may include Young’s modulus.

[0088] In addition, in certain embodiments, creating a CT string design 174 for the CT string 12 (block 240) may include confirming that the CT string design 174 will be capable of a minimum desired reach. In addition, in certain embodiments, creating a CT string design 174 for the CT string 12 (block 240) may include confirming logistical limits associated with the CT string design 174. In addition, in certain embodiments, creating a CT string design 174 for the CT string 12 (block 240) may include confirming that a weight of the CT string design 174 is acceptable. In addition, in certain embodiments, creating a CT string design 174 for the CT string 12 (block 240) may include confirming cost limits, weight-on-bit limits, pull-on-bit limits, and maximum yield stress limits with the CT string design 174. In addition, in certain embodiments, the one or more of the plurality of physical characteristics of the CT string design 174 of the CT string 12 may be adjusted based at least in part on confirmation that one or more key performance indicators for the CT string design 174 are acceptable.

[0089] The embodiments described here optimize CT string designs 174 that can outperform current CT string designs, thereby extending the useful life of a CT string 12 and reducing cost of service delivery (e.g., extending the CT string 12 life by, for example, 20%). In particular, CT string design domain expertise may be captured by the CT String Design and Optimization Tool by, for example, being programmed with algorithms that are capable of utilizing machine learning to automatically identify relationships between various types of CT-related data, as described in greater detail herein.

[0090] In general, the embodiments described herein eliminate a majority of the manual toil required by conventional techniques and reduce the process of designing, optimizing, and validating CT string designs 174. For example, a CT string design currently takes approximately four hours to design and validate. Given that hundreds of varieties of CT strings may be purchased per year, potentially 1,000 (or more) man-hours (e.g., or more than 100 man-days) may be dedicated annually to such CT string designs and associated validations. The embodiments described herein may reduce the process to approximately one hour to design and validate, yielding time savings of approximately 75% or reducing the effort to only 25 man-days or so per year.

[0091] The embodiments described herein may also extract additional value from various discrete engines, simulators, and models through their integration in the CT string design engine and workflows described herein. Furthermore, standardizing CT string designs will reduce the variety of such designs. These standardized designs may then be leveraged by procurement and sourcing functions to secure lower pricing with CT pipe manufacturers.

[0092] The specific embodiments described above have been illustrated by way of example, and it should be understood that these embodiments may be susceptible to various modifications and alternative forms. It should be further understood that the claims are not intended to be limited to the particular forms disclosed, but rather to cover all modifications, equivalents, and alternatives falling within the spirit and scope of this disclosure.

[0093] The techniques presented and claimed herein are referenced and applied to material objects and concrete examples of a practical nature that demonstrably improve the present technical field and, as such, are not abstract, intangible or purely theoretical. Further, if any claims appended to the end of this specification contain one or more elements designated as “means for [perform]ing [a function]...” or “step for [perform]ing [a function]...”, it is intended that such elements are to be interpreted under 35 U.S.C. § 112(f). However, for any claims containing elements designated in any other manner, it is intended that such elements are not to be interpreted under 35 U.S.C. § 112(f).

Claims

1. A method, comprising:

(a) generating a mission profile for a coiled tubing (CT) string for deployment in a well based on CT analytics;

(b) creating a CT string design for the CT string based at least in part on a plurality of operational parameters of the well, wherein the CT string design of the CT string defines a plurality of physical characteristics of the CT string design; and

(c) adjusting one or more of the plurality of physical characteristics of the CT string design of the CT string based at least in part on the generated mission profile for the CT string and a predicted life cycle of the CT string.

2. The method of claim 1, wherein the mission profile for the CT string is generated based at least in part on a location and environment of the well, a basin of the well, or some combination thereof.

3. The method of claim 1, wherein the plurality of operational parameters of the well comprise a hole survey for the well, a total depth of the well, a maximum anticipated wellhead pressure of the well, a maximum reservoir pressure of the well, a maximum temperature of the well, a maximum weight-on-bit of the well, a maximum torque-on-bit of the well, a maximum pump rate of the well, a type of one or more fluids pumped into the well, a minimum annular velocity of the well, a degree to which the well operates in a sour environment, physical characteristics of casings of the well, whether the well is an offshore well or an onshore well, whether the CT is deployed from a fixed platform or a moving vessel, a type of one or more downhole well tools used, or some combination thereof.

4. The method of claim 3, comprising augmenting the mission profile for the CT string of a single well for multiple different wells such that CT pipe of the CT string is optimized against the augmented mission profile.

5. The method of claim 4, wherein the augmented mission profile is defined based on the multiple different wells or as permutations and modulations of the single well.

6. The method of claim 4, wherein the augmented mission profile utilizes sensitivity analysis to modulate one or more of the plurality of operational parameters of the well.

7. The method of claim 1, wherein the plurality of physical characteristics of the CT string comprise a yield strength of metal of the CT string, an outer diameter of the CT string, a wall thickness of the CT string, a length of the CT string, or some combination thereof.

8. The method of claim 1, wherein the plurality of physical characteristics of the CT string comprise Young’s modulus.

9. The method of claim 1, wherein (b) creating a CT string design for the CT string comprises confirming that the CT string design will be capable of a minimum desired reach.

10. The method of claim 1, wherein (b) creating a CT string design for the CT string comprises confirming logistical limits associated with the CT string design.

11. The method of claim 1, wherein (b) creating a CT string design for the CT string comprises confirming that a weight of the CT string design is acceptable.

12. The method of claim 1, wherein (b) creating a CT string design for the CT string comprises confirming cost limits, weight-on-bit limits, pull-on-bit limits, and maximum yield stress limits with the CT string design.

13. The method of claim 1, wherein the one or more of the plurality of physical characteristics of the CT string design of the CT string are adjusted based at least in part on confirmation that one or more key performance indicators for the CT string design are acceptable.

14. The method of claim 1, comprising performing steps (a)-(c) for each of a plurality of combinations of cluster locations, basin identifications, and CT outer diameter size of other CT string designs having similar cluster locations and basin identifications as the well, and having a similar CT outer diameter as the CT string design.

15. A coiled tubing (CT) design analysis system, comprising: one or more processors configured to execute processor-executable instructions stored in memory of the CT design analysis system, wherein the processor-executable instructions, when executed by the one or more processors, cause the CT design analysis system to:

(a) generate a mission profile for a coiled tubing (CT) string for deployment in a well based on CT analytics;

(b) create a CT string design for the CT string based at least in part on a plurality of operational parameters of the well, wherein the CT string design of the CT string defines a plurality of physical characteristics of the CT string design; and

(c) adjust one or more of the plurality of physical characteristics of the CT string design of the CT string based at least in part on the generated mission profile for the CT string and a predicted life cycle of the CT string.

16. The CT design analysis system of claim 15, wherein the mission profile for the CT string is generated based at least in part on a location and environment of the well, a basin of the well, or some combination thereof.

17. The CT design analysis system of claim 15, wherein the plurality of operational parameters of the well comprise a hole survey for the well, a total depth of the well, a maximum anticipated wellhead pressure of the well, a maximum reservoir pressure of the well, a maximum temperature of the well, a maximum weight-on-bit of the well, a maximum torque-on-bit of the well, a maximum pump rate of the well, a type of one or more fluids pumped into the well, a minimum annular velocity of the well, a degree to which the well operates in a sour environment, physical characteristics of casings of the well, whether the well is an offshore well or an onshore well, whether the CT is deployed from a fixed platform or a moving vessel, a type of one or more downhole well tools used, or some combination thereof.

18. The CT design analysis system of claim 15, wherein the plurality of physical characteristics of the CT string comprise a yield strength of metal of the CT string, an outer diameter of the CT string, a wall thickness of the CT string, a length of the CT string, Young’s modulus, or some combination thereof.

19. The CT design analysis system of claim 15, wherein the processor-executable instructions, when executed by the one or more processors, cause the CT design analysis system to perform steps (a)-(c) for each of a plurality of combinations of cluster locations, basin identifications, and CT outer diameter size of other CT string designs having similar cluster locations and basin identifications as the well, and having a similar CT outer diameter as the CT string design.

20. A method, comprising:

(a) generating a mission profile for a coiled tubing (CT) string for deployment in a well based on CT analytics, wherein the mission profile for the CT string is generated based at least in part on a location and environment of the well, a basin of the well, or some combination thereof;

(b) creating a CT string design for the CT string based at least in part on a plurality of operational parameters of the well, wherein the CT string design of the CT string defines a plurality of physical characteristics of the CT string design; and (c) adjusting one or more of the plurality of physical characteristics of the CT string design of the CT string based at least in part on the generated mission profile for the CT string, a predicted life cycle of the CT string, and confirmation that one or more key performance indicators for the CT string design are acceptable.