CN115841247A - Digital drilling risk monitoring method and device - Google Patents

Abstract

The present invention proposes a digital drilling risk monitoring method and device, which relate to the technical field of drilling safety prevention and control. The method includes: acquiring real-time data of the drilling wellbore, describing the actual state of the drilling according to the real-time data of the drilling wellbore, and determining the actual state of the drilling. The actual data of the occurrence state; use the drilling engineering model to simulate the drilling occurrence state, and obtain the predicted data of the drilling occurrence state; compare the well conditions according to the actual data of the actual drilling state and the predicted data of the drilling occurrence state, and determine the drilling risk Index, setting a risk treatment plan according to the drilling risk index; performing drilling rehearsal according to the actual data of the actual drilling state, determining the drilling risk index according to the drilling rehearsal result, and optimizing the drilling operation plan according to the risk treatment plan corresponding to the drilling risk index.

Description

Digital drilling risk monitoring method and device

technical field

The invention relates to the technical field of drilling safety prevention and control, in particular to a digital drilling risk monitoring method and device, which are applicable to real-time monitoring, analysis and diagnosis of potential risk signs during oil and gas well drilling.

Background technique

This section is intended to provide a background or context to embodiments of the invention that are recited in the claims. The descriptions herein are not admitted to be prior art by inclusion in this section.

During the drilling process of oil and gas wells, different geological environments, well types and drilling techniques face different types of drilling accidents and risk probabilities. For example, failure of downhole tools is prone to occur in high-temperature and high-pressure formations, and accidents such as lost circulation and overflow are prone to occur in deep and ultra-deep wells. Pipe sticking accidents are prone to occur in highly deviated wells and horizontal wells.

At present, in response to the above stuck pipe accidents, drilling technicians mainly adopt two methods of passive prevention and active identification to control the risk of downhole accidents. Passive prevention refers to proactively taking measures to avoid drilling risks in accident-prone well sections before downhole accidents occur. However, this method is easy to increase costs; active identification and processing mainly rely on experienced engineers to predict possible downhole accidents based on the changing rules and characteristics of on-site engineering parameters, and take corresponding prevention and corresponding measures. This method is prone to misjudgment and lead to The extension of drilling time will indirectly increase the drilling cost. At the same time, the implementation effect of the above two methods largely depends on the subjective experience of field operators, and it is impossible to make accurate, rapid, and scientific monitoring and diagnosis of potential drilling risks during the drilling process. An effective means for operators to issue early warning information.

The traditional early warning technology of engineering accidents represented by comprehensive mud logging technology measures the operating parameters in real time, and adopts the threshold early warning method to carry out abnormal drilling accident alarms. For early warning, only simple parameter reports can be made for the drill string, well wall and flow in the wellbore. When the early warning is issued, the accident has often deteriorated, and the early warning effect is poor.

In summary, there is an urgent need for a technical solution that can overcome the above defects and provide effective monitoring and early warning for underground accidents.

Contents of the invention

In order to solve the problems existing in the prior art, the present invention proposes a digital drilling risk monitoring method and device; the method and device are based on dynamic simulation data and real-time data reflecting system status, and realize complex analysis of accidents that will occur in the wellbore And timely warning, and by analyzing and simulating the changes in construction results under different construction parameters and working conditions in the process of drilling and completion operations, it helps engineering operators determine reasonable drilling engineering measures to avoid accident risks.

In the first aspect of the embodiments of the present invention, a digital drilling risk monitoring method is proposed, including:

Obtain real-time data of the drilling wellbore, describe the actual state of the drilling according to the real-time data of the drilling wellbore, and determine the actual data of the actual state of the drilling;

Use the drilling engineering model to simulate the state of the drilling occurrence, and obtain the prediction data of the drilling occurrence state;

Comparing the well conditions according to the actual data of the actual drilling state and the predicted data of the drilling state, determining the drilling risk index, and setting a risk treatment plan according to the drilling risk index;

Drilling rehearsal is performed according to the actual data of the actual drilling state, the drilling risk index is determined according to the drilling rehearsal result, and the drilling operation plan is optimized according to the risk treatment plan corresponding to the drilling risk index.

In the second aspect of the embodiments of the present invention, a digital drilling risk monitoring device is proposed, including:

The multivariate data acquisition module is used to obtain real-time data of the drilling wellbore, describe the actual state of the drilling according to the real-time data of the drilling wellbore, and determine the actual data of the actual state of the drilling;

The calculation and simulation module is used for simulating the drilling occurrence state by using the drilling engineering model, and obtaining the prediction data of the drilling occurrence state;

The drilling risk analysis module is used to compare the well conditions according to the actual data of the actual drilling state and the predicted data of the drilling state, determine the drilling risk index, and set the risk treatment plan according to the drilling risk index;

The operation plan optimization module is used to perform drilling rehearsal according to the actual data of the actual drilling state, determine the drilling risk index according to the drilling rehearsal result, and optimize the drilling operation plan according to the risk treatment plan corresponding to the drilling risk index.

In the third aspect of the embodiments of the present invention, a computer device is proposed, including a memory, a processor, and a computer program stored in the memory and operable on the processor, and the processor implements the computer program to realize digitization Drilling risk monitoring method.

In the fourth aspect of the embodiments of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, a digital drilling risk monitoring method is implemented.

In the fifth aspect of the embodiments of the present invention, a computer program product is proposed, the computer program product includes a computer program, and when the computer program is executed by a processor, a digital drilling risk monitoring method is implemented.

The digital drilling risk monitoring method and device proposed by the present invention can solve the problem of hysteresis in traditional drilling safety early warning technology and the inability to realize risk assessment and prediction. The present invention uses digital information description, digital prediction and analysis, digital analysis and diagnosis, digital preview optimization and other processes , realize the transformation of drilling safety early warning from abnormal parameter report to accident risk prediction, and support the development of scientific and automatic drilling technology in the future.

Description of drawings

In order to illustrate the technical solutions of the embodiments of the present application more clearly, the drawings that need to be used in the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are some embodiments of the present application. Ordinary technicians can also obtain other drawings based on these drawings without paying creative work.

Fig. 1 is a schematic flowchart of a digital drilling risk monitoring method according to an embodiment of the present invention.

Fig. 2 is a schematic flow chart of digital well description according to an embodiment of the present invention.

Fig. 3 is a schematic flow chart of digital well condition prediction according to an embodiment of the present invention.

Fig. 4 is a schematic flow chart of digital well condition analysis according to an embodiment of the present invention.

Fig. 5 is a schematic flow chart of digital well condition preview according to an embodiment of the present invention.

Fig. 6 is a schematic flow chart of digital drilling risk monitoring according to a specific embodiment of the present invention.

Fig. 7 is a schematic diagram of a calculation result of standpipe pressure according to a specific embodiment of the present invention.

Fig. 8 is a schematic diagram of calculation results of the hook load according to a specific embodiment of the present invention.

Fig. 9 is a schematic diagram of calculation results of torque according to a specific embodiment of the present invention.

Fig. 10 is a schematic diagram of hook load, riser pressure deviation rate and change rate of an example well according to a specific embodiment of the present invention.

Fig. 11 is a schematic diagram of the variation of the wellbore stuck pipe risk early warning index with the well depth of an example of a specific embodiment of the present invention.

Fig. 12 is a schematic diagram of calibration of wellbore friction coefficient based on bottom-hole WOB and torque parameters in an example well according to an embodiment of the present invention.

Fig. 13 is a schematic diagram of the structure of a digital drilling risk monitoring device according to an embodiment of the present invention.

Fig. 14 is a schematic diagram of the structure of the calculation and simulation module of a specific embodiment of the present invention.

Fig. 15 is a schematic structural diagram of a computer device according to an embodiment of the present invention.

Detailed ways

The principle and spirit of the present invention will be described below with reference to several exemplary embodiments. It should be understood that these embodiments are given only to enable those skilled in the art to better understand and implement the present invention, rather than to limit the scope of the present invention in any way. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

Those skilled in the art know that the embodiments of the present invention can be implemented as a system, device, device, method or computer program product. Therefore, the present disclosure may be embodied in the form of complete hardware, complete software (including firmware, resident software, microcode, etc.), or a combination of hardware and software.

According to the embodiments of the present invention, a digital drilling risk monitoring method and device are proposed, which relate to the technical field of drilling safety prevention and control. Aiming at the problems existing in the drilling risk monitoring technology and combining the characteristics of the digital twin technology, the present invention proposes a digital twin method applied to the drilling process including digital information description, digital predictive analysis, digital analysis diagnosis, digital preview optimization and other processes, forming A new and feasible digital drilling risk monitoring method was developed, and a corresponding software system was designed.

The principle and spirit of the present invention will be explained in detail below with reference to several representative embodiments of the present invention.

Fig. 1 is a schematic flowchart of a digital drilling risk monitoring method according to an embodiment of the present invention. As shown in Figure 1, the method includes:

S1. Obtain real-time data of the drilling wellbore, describe the actual state of the drilling according to the real-time data of the drilling wellbore, and determine the actual data of the actual state of the drilling;

S2, using the drilling engineering model to simulate the state of the drilling occurrence, and obtain the prediction data of the drilling occurrence state;

S3, comparing the well conditions according to the actual data of the actual drilling state and the predicted data of the drilling state, determining the drilling risk index, and setting a risk treatment plan according to the drilling risk index;

S4. Carry out drilling rehearsal according to the actual data of the actual drilling state, determine the drilling risk index according to the drilling rehearsal result, and optimize the drilling operation plan according to the risk treatment plan corresponding to the drilling risk index.

According to the dynamic simulation data and the real-time data reflecting the system state, the present invention realizes complex analysis and timely warning of accidents that will occur in the wellbore, and analyzes and simulates the changes of construction results under different construction parameters and working conditions in the process of drilling and completion operations , to help engineering operators determine reasonable drilling engineering measures to avoid accident risks.

In practical application scenarios, while effectively solving the lagging problem of traditional drilling safety early warning technology, it provides a complex solution for on-site drilling operations to avoid downhole accidents, and realizes the transformation of drilling safety early warning from parameter abnormal report to accident risk prediction and active prevention. Support the development of future scientific and automated drilling technology.

In order to explain more clearly the above digital drilling risk monitoring method, each step will be described in detail below.

In S1, referring to Fig. 2, the real-time data of the drilling wellbore is obtained, the actual drilling state is described according to the real-time data of the drilling wellbore, and the detailed process for determining the actual data of the actual drilling state is as follows:

S101, receiving the real-time data of the drilling wellbore through the comprehensive logging tool and the LWD/MWD instrument;

S102, establish a standard real-time data object of the drilling wellbore according to time, depth, working condition and specialty, design a corresponding relational data table structure, build a database according to the relational database structure, and store the real-time data of the drilling wellbore;

S103. Describe the actual data of the actual drilling state according to the real-time data of the drilling wellbore; wherein, the actual data of the actual drilling state at least include: hook load, torque and standpipe pressure.

Specifically, develop a standard network communication interface for the integrated mud logging instrument and LWD/MWD instrument interface to realize real-time data reception of the drilling wellbore; establish standard real-time data objects for the drilling wellbore according to time, depth, working condition, specialty, etc. and design corresponding The relational data table structure, relying on the relational database management key to build the database, realize the real-time data storage of the drilling wellbore, and then describe the state of the drilling.

In S2, referring to Figure 3, the drilling engineering model is used to simulate the state of the drilling occurrence, and the detailed process for obtaining the prediction data of the drilling occurrence state is as follows:

S201, collect data on wellbore structure, drilling tool assembly, drilling fluid performance and wellbore trajectory to be analyzed on site, use the drilling hydraulics model to predict the standpipe pressure at different well depths, and store the calculation results in the database;

S202, according to the wellbore structure, drilling tool assembly, drilling fluid performance, and borehole trajectory data to be analyzed on site, use the drill string mechanics model to predict the hook load and torque at different working conditions and well depth positions, and store the results in the database .

Specifically, for the downhole wellbore environment composed of drill string, well wall and annular fluid, the industry standard friction torque model, rock mechanics model and hydraulic model are used to model and predict the key data of the wellbore state. The segmentation unit outputs the calculation results of the original model such as the lateral force, axial force, frictional resistance, torque force, and cycle pressure loss of the drilling tool, and adopts an iterative calculation method along the well extension to obtain any well depth step that can be used for actual drilling The drilling wellbore prediction engineering data compared with the data, and then simulate the state of the drilling is taking place.

In S3, referring to Fig. 4, the well condition is compared according to the actual data of the actual drilling state and the predicted data of the drilling state, the drilling risk index is determined, and the specific flow of the risk treatment plan is set according to the drilling risk index for:

S301. Calculate the deviation value, deviation rate, change value, and change rate between the actual data of the actual drilling state and the predicted data of the drilling state;

Specifically, the calculation formula is as follows:

Y _Deviation = X _Actual - X _Predicted

Y _{change value} = X ₂ -X ₁

Among them, X _prediction is the predicted hook load, torque and standpipe pressure value, the unit of hook load is N, the unit of torque is N m, and the unit of standpipe pressure is Pa;

_Xactual is the actually collected hook load, torque, and riser pressure values, the hook load unit is N, the torque unit is N m, and the standpipe pressure unit is Pa;

X ₁ is the average value of hook load, torque, and standpipe pressure in the first set cycle, the default time interval of the first cycle is 30s, the unit of hook load is N, the unit of torque is N m, and the unit of standpipe pressure is Pa;

X ₂ is the average value of hook load, torque and standpipe pressure in the second set cycle, the default time interval of the second cycle is 30s, the unit of hook load is N, the unit of torque is N m, and the unit of standpipe pressure is Pa.

S302, according to the deviation value, deviation rate, change value, and change rate between the actual data of the actual drilling state and the predicted data of the drilling state, use the pipe sticking risk early warning model to form a wellbore stuck pipe risk early warning index;

S303. Quantify the risk treatment plan according to the drilling risk index, wherein, when the index is less than A%, set it as low risk, prompting normal drilling operations; when the index is greater than A% and less than B%, set it as medium risk, prompting On-site operators need to pay attention to changes in wellbore conditions; when the index is greater than B%, set it as a high risk, prompting on-site operators to start the pump cycle, slowly lift and lower, and continue to observe.

Specifically, compare the actual wellbore data with the predicted wellbore data in real time to obtain the deviation value, deviation rate (0-100%), change value, and change rate (0-100%); through the deviation value, deviation rate, change value, The rate of change defines a risk index that quantifies the severity of different accident risks in real time.

In S4, referring to Fig. 5, the drilling rehearsal is performed according to the actual data of the actual drilling state, the drilling risk index is determined according to the drilling rehearsal result, and the specific process of optimizing the drilling operation plan according to the risk treatment plan corresponding to the drilling risk index is as follows:

S401, performing drilling rehearsal according to the real-time data of the drilling occurrence state, and obtaining the drilling rehearsal result;

S402. Carry out sensitivity analysis according to the drilling rehearsal results, determine the bottom hole drilling pressure and torque parameters to avoid the risk of drilling accidents, and determine the wellbore stuck pipe risk index after completing the wellbore friction coefficient check;

S403. Optimizing the drilling operation plan according to the risk treatment plan corresponding to the drilling risk index.

Specifically, the real-time wellbore data is introduced into the digital well condition prediction process, and the follow-up drilling plan is previewed and diagnosed according to the digital well condition prediction process, and the risk index of the subsequent construction well section is obtained, and the operation parameters under low risk conditions are obtained according to the risk index. Guide the next step of drilling construction.

It should be noted that although the operations of the method of the present invention are described in a specific order in the above-mentioned embodiments and accompanying drawings, this does not require or imply that these operations must be performed in this specific order, or that all shown operations must be performed. operation to achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step for execution, and/or one step may be decomposed into multiple steps for execution.

In order to explain the above digital drilling risk monitoring method more clearly, a specific embodiment will be used for illustration below.

Taking a well area as an example, referring to the schematic diagram of the digital drilling risk monitoring process in Figure 6, digital drilling risk monitoring is performed on the drilling operations in the well area.

S61, the digital well condition description process.

The real-time data of the drilling wellbore is acquired, the actual state of the drilling is described according to the real-time data of the drilling wellbore, and the actual data of the actual state of the drilling is determined.

Set network communication specifications according to the data interface of the comprehensive logging tool, receive real-time drilling engineering data such as hook load, torque, and riser pressure in real time, and use the standard MS SQL Server database for storage.

In this embodiment, the network communication standard may adopt the TCP/IP WITS0 standard.

Specifically, engineering data such as hook load, torque, and standpipe pressure sent by the comprehensive mud logging tool of the example well is received, and the engineering data is marked in the format AABBCCC;

Among them, AA represents the data sequence category, 01 represents the time series, and 02 represents the depth sequence data;

BB represents the parameter mark ID, which is a 2-digit number from 01-99;

CCC stands for parameter value.

In this embodiment, the hook load data is marked as 0114CCC, the torque data is marked as 0108CCC, and the standpipe pressure data is marked as 0120CCC, and the specific value of each parameter depends on the measured value of the data.

Use MS SQL Server to create a database named Alarm, and create a table named Time_RealTime_Data, and the field names are wid (type is varchar (50)), datetime (type is DateTime), hkload (type is decimal), torque ( type decimal), spp (type decimal). According to the above format definition, engineering data such as hook load, torque and standpipe pressure can be stored in real-time in the MS SQL Server database for subsequent extraction and analysis.

S62, digital well condition prediction process:

The drilling engineering model is used to simulate the drilling occurrence state and obtain the prediction data of the drilling occurrence state. The prediction data at least include: standpipe pressure, hook load, torque value and other data.

The calculation of the standpipe pressure will be described in detail below.

Collect the wellbore structure, drilling tool assembly, drilling fluid performance, and wellbore trajectory data to be analyzed on site, use the drilling hydraulics model to predict the standpipe pressure at different well depths, and store the calculation results in the database.

Example well calculation standpipe pressure The key parameters involved in the specific calculation method are as shown in Table 1, the pressure gradient can be multiplied by the depth of the well to obtain the standpipe pressure; as shown in Figure 7, it is the standpipe pressure of a specific embodiment of the present invention Schematic diagram of calculation results.

Table 1. Key parameters for calculating standpipe pressure

In the calculation formula in Table 1, ρ is the drilling fluid density, g/cm3;

d is the inner diameter of the drilling tool, m;

D is the outer diameter of the drilling tool, m;

Q is the drilling fluid displacement (flow rate), m ³ /s;

R ₆₀₀ is the reading of the drilling fluid at a rotation speed of 600r/min, dimensionless;

R ₃₀₀ is the reading of the drilling fluid at a rotation speed of 300r/min, dimensionless;

R ₁₀₀ is the reading of the drilling fluid at a rotation speed of 100r/min, dimensionless;

R ₃ is the reading of the drilling fluid at a rotary viscometer speed of 3r/min, dimensionless;

The calculation of hook load and torque values will be described in detail below.

Collect the wellbore structure, drilling tool assembly, drilling fluid performance, and borehole trajectory data to be analyzed on site, use the drill string mechanics calculation model to predict the hook load and torque values at different working conditions and well depth positions, and store the results in the database .

The key parameters involved in calculating the hook load and torque in the example well are shown in Table 2, and the hook load and torque can be obtained according to the recursive formula of different working conditions; as shown in Figure 8, it is a specific embodiment of the present invention The schematic diagram of the calculation result of the hook load; as shown in FIG. 9 , it is a schematic diagram of the calculation result of the torque of a specific embodiment of the present invention.

Table 2 Calculation of key parameters of hook load and torque under different working conditions

分别为单元管柱所在测段上下两测点的井斜角和方位角，rad；Among them, α ₁ , α ₂ ,

Respectively, the inclination and azimuth angles of the upper and lower measuring points in the measuring section where the unit pipe string is located, rad;

W _b is the buoyant weight of the unit string, N;

T ₂ is the axial force on the lower end surface of the unit string, N;

γ is the dogleg angle of the measuring section where the unit string is located, rad;

N _r is the contact positive pressure between the unit string and the well wall, N;

E is the elastic modulus of the string material, Pa/m ² ;

I is the bending moment of inertia of the string, m ⁴ ;

K' is borehole curvature, rad/m;

L is the length of the pipe string to be analyzed, m;

_Dw is borehole diameter, m;

D _o is the outer diameter of the pipe string, m;

f' is the comprehensive friction coefficient of drill string and wellbore;

F is the frictional resistance of the unit string, N.

S63, digital well condition analysis process:

Comparing the well conditions according to the actual data of the actual drilling state and the predicted data of the drilling state, determining the drilling risk index, and setting a risk treatment plan according to the drilling risk index.

Real-time calculation of actual and predicted hook load, torque, riser pressure deviation value, change value, deviation rate, change rate and calculation of stuck pipe risk index, deviation value, change value, deviation rate, change rate;

Specifically, the calculation method is as follows:

Y _Deviation = X _Actual - X _Predicted

Y _{change value} = X ₂ -X ₁

Among them, X _prediction is the predicted hook load, torque and standpipe pressure value, the unit of hook load is N, the unit of torque is N m, and the unit of standpipe pressure is Pa;

_Xactual is the actually collected hook load, torque, and riser pressure values, the hook load unit is N, the torque unit is N m, and the standpipe pressure unit is Pa;

X ₁ is the average value of hook load, torque, and standpipe pressure in the first set cycle, the default time interval of the first cycle is 30s, the unit of hook load is N, the unit of torque is N m, and the unit of standpipe pressure is Pa;

X ₂ is the average value of hook load, torque and standpipe pressure in the second cycle, the default time interval of the second cycle is 30s, the unit of hook load is N, the unit of torque is N m, and the unit of standpipe pressure is Pa.

During the drilling process, according to the calculated theoretical load, torque, riser parameters and actual parameter deviation rate, as well as the actual drilling ground load, torque, and riser parameter change rate, the wellbore engineering parameter changes and deviations during the drilling process are determined; as shown in the figure 10 is a schematic diagram of hook load, riser pressure deviation rate and change rate of an example well according to a specific embodiment of the present invention.

According to the deviation rate of the actual engineering parameter value and the predicted engineering parameter and the change rate of the actual drilling engineering parameter, the wellbore stuck pipe risk early warning index is formed based on the system's built-in pipe stuck risk early warning model; among them,

When the index is less than A%, it is set to low-risk green, and drilling operations can be carried out normally;

When the index is greater than A% and less than B%, it is set to medium risk yellow, and field operators need to pay attention to changes in wellbore conditions;

When the index is greater than B%, it is set to high-risk red, and on-site operators need to take measures such as turning on the pump to circulate, slowly lifting and lowering to observe, etc. to improve the wellbore working conditions.

As shown in FIG. 11 , it is a schematic diagram of the variation of the wellbore stuck pipe risk early warning index with the well depth of an example of a specific embodiment of the present invention.

S64, digital well condition preview process:

Drilling rehearsal is carried out according to the actual data of the actual drilling state, the drilling risk index is determined according to the drilling rehearsal result, and the drilling operation plan is optimized according to the risk treatment plan corresponding to the drilling risk index:

Combined with the actual drilling engineering parameters to conduct sensitivity analysis, determine the optimal bottom hole WOB and torque parameters that can ensure the accuracy of early warning of pipe sticking risk, and determine the wellbore pipe sticking risk index after completing the wellbore friction coefficient check.

As shown in FIG. 12 , it is a schematic diagram of checking the wellbore friction coefficient based on bottom-hole WOB and torque parameters in an example well according to an embodiment of the present invention. In the figure, the friction coefficient of the casing section is calculated as 0.2 under the drilling condition, and the friction coefficient of the open hole section is 0.25, 0.3 and 0.4 respectively. The hook load sensitivity curve is determined by comparing with the measured hook load. At this time, the hook load, torque and standpipe pressure are recalculated for the given downhole WOB and torque to ensure that the current drilling parameters calculated by the stuck pipe risk warning model are optimal.

After introducing the method of the exemplary embodiment of the present invention, next, the digital drilling risk monitoring device of the exemplary embodiment of the present invention will be introduced with reference to FIG. 13 .

For the implementation of the digital drilling risk monitoring device, reference can be made to the implementation of the above method, and the repetition will not be repeated. The term "module" or "unit" used below may be a combination of software and/or hardware that realizes predetermined functions. Although the devices described in the following embodiments are preferably implemented in software, implementations in hardware, or a combination of software and hardware are also possible and contemplated.

Based on the same inventive concept, the present invention also proposes a digital drilling risk monitoring device, as shown in Figure 13, the device includes:

The multivariate data acquisition module 110 is used to acquire real-time data of the drilling wellbore, describe the actual state of the drilling according to the real-time data of the drilling wellbore, and determine the actual data of the actual state of the drilling;

Calculation and simulation module 120, used for simulating the occurrence state of drilling by using the drilling engineering model, and obtaining the prediction data of the occurrence state of drilling;

The drilling risk analysis module 130 is used to compare the well conditions according to the actual data of the actual drilling state and the predicted data of the drilling state, determine the drilling risk index, and set a risk treatment plan according to the drilling risk index;

The operation plan optimization module 140 is used to perform drilling rehearsal according to the actual data of the actual drilling state, determine the drilling risk index according to the drilling rehearsal result, and optimize the drilling operation plan according to the risk treatment plan corresponding to the drilling risk index.

In one embodiment, the multivariate data acquisition module 110 is specifically used for:

Receive real-time data of drilling wellbore through integrated mud logging unit and LWD/MWD instrument;

Establish standard real-time data objects of drilling wellbore according to time, depth, working conditions and specialty, design corresponding relational data table structure, build database according to relational database structure, and store real-time data of drilling wellbore;

According to the real-time data of the drilling wellbore, the actual data of the actual drilling state is described; wherein, the actual data of the actual drilling state at least includes: hook load, torque and standpipe pressure.

Specifically, the multivariate data acquisition module 110 performs network communication with the drilling field instruments, and uses TCP/IP, UDP/IP, Series, and Modbus network communication interfaces to analyze the network data to the local in real time.

In one embodiment, the calculation and simulation module 120 is specifically used for:

Collect the wellbore structure, drilling tool assembly, drilling fluid performance and wellbore trajectory data to be analyzed on site, use the drilling hydraulics model to predict the standpipe pressure at different well depths, and store the calculation results in the database;

According to the wellbore structure, drilling tool assembly, drilling fluid performance and wellbore trajectory data to be analyzed on site, the drill string mechanics model is used to predict the hook load and torque at different working conditions and well depth positions, and the results are stored in the database.

In a specific embodiment, refer to FIG. 14 , which is a schematic structural diagram of a computing simulation module. As shown in Figure 14, the calculation simulation module includes:

The drilling hydraulics calculation and simulation unit 121 is used to realize the process of digital well condition prediction, simulate and calculate the fluid hydraulics of the wellbore annular space, and realize the hydraulic parameters of the annular space such as fluctuating pressure, wellbore cleanliness, circulation pressure loss, and standpipe pressure to analyze;

The drill string mechanics calculation and simulation unit 122 is used to realize the process of digital well condition prediction, to simulate and calculate the wellbore drill string objects, and to realize the analysis of drill string parameters such as drilling tool friction, ground torque, and ground hook load under different working conditions;

Drilling rock mechanics calculation and simulation unit 123 is used to realize the process of digital well condition prediction, to simulate and calculate well borehole wall objects, and to analyze rock drillability, brittleness, strength and formation pressure.

In one embodiment, the drilling risk analysis module 130 is specifically used for:

Calculate the actual data of the actual state of drilling and the deviation value, deviation rate, change value, and rate of change of the predicted data of the state of occurrence of the drilling, and the calculation formula is as follows:

Y _Deviation = X _Actual - X _Predicted

Y _{change value} = X ₂ -X ₁

Among them, X _prediction is the predicted hook load, torque and standpipe pressure value, the unit of hook load is N, the unit of torque is N m, and the unit of standpipe pressure is Pa;

_Xactual is the actually collected hook load, torque, and riser pressure values, the hook load unit is N, the torque unit is N m, and the standpipe pressure unit is Pa;

X ₁ is the average value of hook load, torque, and standpipe pressure in the first set cycle, the default time interval of the first cycle is 30s, the unit of hook load is N, the unit of torque is N m, and the unit of standpipe pressure is Pa;

X ₂ is the average value of hook load, torque and standpipe pressure in the second cycle, the default time interval of the second cycle is 30s, the unit of hook load is N, the unit of torque is N m, and the unit of standpipe pressure is Pa.

In one embodiment, the drilling risk analysis module 130 is specifically used for:

According to the deviation value, deviation rate, change value, and change rate between the actual data of the actual drilling state and the predicted data of the drilling state, the wellbore stuck pipe risk early warning index is formed by using the pipe stuck risk early warning model;

Quantify the risk treatment plan according to the drilling risk index, wherein, when the index is less than A%, set it as low risk, prompting normal drilling operations; when the index is greater than A% and less than B%, set it as medium risk, prompting on-site operations Personnel need to pay attention to changes in wellbore working conditions; when the index is greater than B%, it is set as a high risk, prompting field operators to start the pump cycle, slowly lift and lower, and continue to observe.

In one embodiment, the operation plan optimization module 140 is specifically used for:

Drilling rehearsal is performed according to the real-time data of drilling occurrence status, and the result of drilling rehearsal is obtained;

Carry out sensitivity analysis based on drilling preview results, determine bottom hole drilling pressure and torque parameters to avoid the risk of drilling accidents, and determine the wellbore sticking risk index after completing the wellbore friction coefficient check;

Optimize the drilling operation plan according to the risk treatment plan corresponding to the drilling risk index.

It should be noted that although several modules of the digital drilling risk monitoring device are mentioned in the above detailed description, this division is only exemplary and not mandatory. Actually, according to the embodiment of the present invention, the features and functions of two or more modules described above may be embodied in one module. Conversely, the features and functions of one module described above may be further divided to be embodied by a plurality of modules.

Based on the foregoing inventive concepts, as shown in FIG. 15 , the present invention also proposes a computer device 1500, including a memory 1510, a processor 1520, and a computer program 1530 stored in the memory 1510 and operable on the processor 1520. When the processor 1520 executes the computer program 1530, the foregoing digital drilling risk monitoring method is realized.

Based on the aforementioned inventive concept, the present invention proposes a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, implements the aforementioned digital drilling risk monitoring method.

Based on the aforementioned inventive concept, the present invention proposes a computer program product, the computer program product includes a computer program, and when the computer program is executed by a processor, a digital drilling risk monitoring method is implemented.

The digital drilling risk monitoring method and device proposed by the present invention can solve the problem of hysteresis in traditional drilling safety early warning technology and the inability to realize risk assessment and prediction. The present invention uses digital information description, digital prediction and analysis, digital analysis and diagnosis, digital preview optimization and other processes , realize the transformation of drilling safety early warning from abnormal parameter report to accident risk prediction, and support the development of scientific and automatic drilling technology in the future.

Those skilled in the art should understand that the embodiments of the present invention may be provided as methods, apparatuses, or computer program products. Accordingly, the present invention can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods and computer program products according to embodiments of the invention. It should be understood that each procedure and/or block in the flowchart and/or block diagram, and a combination of procedures and/or blocks in the flowchart and/or block diagram can be realized by computer program instructions. These computer program instructions may be provided to a general purpose computer, special purpose computer, embedded processor, or processor of other programmable data processing equipment to produce a machine such that the instructions executed by the processor of the computer or other programmable data processing equipment produce a An apparatus for realizing the functions specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to operate in a specific manner, such that the instructions stored in the computer-readable memory produce an article of manufacture comprising instruction means, the instructions The device realizes the function specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

These computer program instructions can also be loaded onto a computer or other programmable data processing device, causing a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented process, thereby The instructions provide steps for implementing the functions specified in the flow chart or blocks of the flowchart and/or the block or blocks of the block diagrams.

Finally, it should be noted that: the above-described embodiments are only specific implementations of the present invention, used to illustrate the technical solutions of the present invention, rather than limiting them, and the scope of protection of the present invention is not limited thereto, although referring to the foregoing The embodiment has described the present invention in detail, and those skilled in the art should understand that any person familiar with the technical field can still modify the technical solutions described in the foregoing embodiments within the technical scope disclosed in the present invention Changes can be easily thought of, or equivalent replacements are made to some of the technical features; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the scope of the present invention within the scope of protection. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims (15)

1. A digital drilling risk monitoring method is characterized by comprising the following steps:

acquiring real-time data of a drilling shaft, describing the actual occurrence state of the drilling according to the real-time data of the drilling shaft, and determining the actual data of the actual occurrence state of the drilling;

simulating a drilling occurrence state by using a drilling engineering model, and acquiring prediction data of the drilling occurrence state;

comparing well conditions according to the actual data of the actual occurrence state of the well drilling and the predicted data of the occurrence state of the well drilling, determining a well drilling risk index, and setting a risk processing scheme according to the well drilling risk index;

and performing drilling previewing according to the actual data of the actual drilling occurrence state, determining a drilling risk index according to a drilling previewing result, and optimizing a drilling operation scheme according to a risk processing scheme corresponding to the drilling risk index.

2. The method of claim 1, wherein obtaining real-time data from a wellbore, describing actual conditions of occurrence of the wellbore from the real-time data from the wellbore, and determining actual data from the actual conditions of occurrence of the wellbore comprises:

receiving real-time data of a drilling shaft through a comprehensive logging instrument and an LWD/MWD instrument;

establishing a standard drilling shaft real-time data object according to time, depth, working conditions and specialities, designing a corresponding relational data table structure, establishing a database according to the relational database structure, and storing the real-time data of the drilling shaft;

describing actual data of the actual occurrence state of the drilling well according to the real-time data of the drilling well shaft; wherein the actual data of the actual occurrence of the well comprises at least: hook load, torque and riser pressure.

3. The method of claim 1, wherein simulating the well drilling occurrence using the well drilling engineering model to obtain predictive data of the well drilling occurrence comprises:

collecting the well body structure, the drilling tool assembly, the drilling fluid performance and the well track data of a shaft to be analyzed on site, predicting the pressure of a vertical pipe at different well depth positions by using a drilling hydraulics model, and storing the calculation result into a database;

according to the structure of a shaft body of a shaft to be analyzed, a drilling tool assembly, the performance of drilling fluid and well track data on site, hook loads and torques at different working conditions and well depth positions are predicted by utilizing a drill string mechanical model, and the results are stored in a database.

4. The method of claim 1, wherein comparing the well conditions based on the actual data of the actual occurrence of the well and the predicted data of the occurrence of the well to determine a well risk index, and setting a risk handling plan based on the well risk index comprises:

calculating deviation value, deviation rate, change value and change rate of the actual data of the actual occurrence state of the drilling well and the predicted data of the occurrence state of the drilling well, wherein the calculation formula is as follows:

Y _{deviation value} ＝X _{Practice of} -X _Prediction

Y _{Variation value} ＝X ₂ -X ₁

Wherein, X _Prediction The predicted values of the hook load, the torque and the pressure of the vertical pipe are obtained, wherein the unit of the hook load is N, the unit of the torque is N.m, and the unit of the pressure of the vertical pipe is Pa;

X _{practice of} The method comprises the following steps of (1) actually collecting hook load, torque and riser pressure values, wherein the unit of the hook load is N, the unit of the torque is N.m, and the unit of the riser pressure is Pa;

X ₁ setting the average values of the hook load, the torque and the riser pressure in a first period, wherein the default time interval of the first period is 30s, the unit of the hook load is N, the unit of the torque is N.m, and the unit of the riser pressure is Pa;

X ₂ the mean values of hook load, torque, riser pressure in the second period are set, the default time interval for the second period is 30s, hook load in units of N, torque in units of N · m, riser pressure in units of Pa.

5. The method of claim 4, wherein comparing the well conditions based on the actual data of the actual occurrence of the well and the predicted data of the occurrence of the well determines a well risk index, and setting a risk handling scheme based on the well risk index comprises:

forming a shaft stuck drill risk early warning index by using a stuck drill risk early warning model according to the deviation value, the deviation rate, the change value and the change rate of the actual data of the actual occurrence state of the drilling well and the predicted data of the occurrence state of the drilling well;

quantifying a risk processing scheme according to the drilling risk index, wherein when the index is less than A%, setting the risk as low risk, and prompting normal drilling operation; when the index is larger than A% and smaller than B%, setting the index as a medium risk, and prompting field operators to pay attention to the change of the working condition of the shaft; when the index is larger than B%, setting the index as high risk, prompting field operators to start the pump for circulation, slowly lift and place the pump and continuously observe the pump.

6. The method of claim 1, wherein drilling previews are performed according to actual data of the actual occurrence state of the drilling well, drilling risk indexes are determined according to drilling previewing results, and drilling operation schemes are optimized according to risk processing schemes corresponding to the drilling risk indexes, and the method comprises the following steps:

drilling forecasting is carried out according to the real-time data of the drilling occurrence state to obtain a drilling forecasting result;

carrying out sensitivity analysis according to a drilling prediction result, determining bottom hole drilling pressure and torque parameters for avoiding drilling accident risks, and determining a shaft sticking risk index after completing shaft friction coefficient check;

and optimizing a drilling operation scheme according to the risk processing scheme corresponding to the drilling risk index.

7. A digital drilling risk monitoring device, comprising:

the multivariate data acquisition module is used for acquiring real-time data of a drilling shaft, describing the actual occurrence state of the drilling according to the real-time data of the drilling shaft and determining the actual data of the actual occurrence state of the drilling;

the calculation simulation module is used for simulating the drilling occurrence state by using the drilling engineering model and acquiring the prediction data of the drilling occurrence state;

the drilling risk analysis module is used for comparing well conditions according to the actual data of the actual occurrence state of the drilling well and the predicted data of the occurrence state of the drilling well, determining a drilling risk index and setting a risk processing scheme according to the drilling risk index;

and the operation scheme optimization module is used for conducting drilling previewing according to the actual data of the actual drilling occurrence state, determining a drilling risk index according to a drilling previewing result, and optimizing a drilling operation scheme according to a risk processing scheme corresponding to the drilling risk index.

8. The apparatus of claim 7, wherein the multivariate data acquisition module is specifically configured to:

receiving real-time data of a drilling shaft through a comprehensive logging instrument and an LWD/MWD instrument;

establishing a standard drilling shaft real-time data object according to time, depth, working conditions and specialities, designing a corresponding relational data table structure, establishing a database according to the relational database structure, and storing the real-time data of the drilling shaft;

describing actual data of the actual occurrence state of the drilling well according to the real-time data of the drilling well shaft; wherein the actual data of the actual occurrence of the well comprises at least: hook load, torque, and riser pressure.

9. The apparatus of claim 7, wherein the computational simulation module is specifically configured to:

collecting the well body structure, the drilling tool assembly, the drilling fluid performance and the well track data of a shaft to be analyzed on site, predicting the pressure of a vertical pipe at different well depth positions by using a drilling hydraulics model, and storing the calculation result into a database;

according to the structure of a shaft body of a shaft to be analyzed, a drilling tool assembly, the performance of drilling fluid and well track data on site, hook loads and torques at different working conditions and well depth positions are predicted by utilizing a drill string mechanical model, and the results are stored in a database.

10. The apparatus of claim 7, wherein the drilling risk analysis module is specifically configured to:

calculating deviation value, deviation rate, change value and change rate of the actual data of the actual occurrence state of the drilling well and the predicted data of the occurrence state of the drilling well, wherein the calculation formula is as follows:

Y _{deviation value} ＝X _{Practice of} -X _Prediction

Y _{Variation value} ＝X ₂ -X ₁

Wherein, X _Prediction The predicted values of the hook load, the torque and the pressure of the vertical pipe are obtained, wherein the unit of the hook load is N, the unit of the torque is N.m, and the unit of the pressure of the vertical pipe is Pa;

X _{in fact} The method comprises the following steps of (1) actually collecting hook load, torque and riser pressure values, wherein the unit of the hook load is N, the unit of the torque is N.m, and the unit of the riser pressure is Pa;

X ₁ setting the average values of hook load, torque and riser pressure in a first period, wherein the default time interval of the first period is 30s, the unit of hook load is N, the unit of torque is N.m, and the unit of riser pressure is Pa;

X ₂ setting the mean values of the hook load, the torque and the pressure of the riser in a second period, wherein the default time interval of the second period is 30s, the unit of the hook load is N, the unit of the torque is N.m, and the unit of the riser is N.mThe pressure unit is Pa.

11. The apparatus of claim 10, wherein the drilling risk analysis module is specifically configured to:

forming a shaft stuck drill risk early warning index by using a stuck drill risk early warning model according to the deviation value, deviation rate, change value and change rate of the actual data of the actual occurrence state of the drilled well and the predicted data of the occurrence state of the drilled well;

quantifying a risk processing scheme according to the drilling risk index, wherein when the index is less than A%, setting the risk as low risk, and prompting normal drilling operation; when the index is larger than A% and smaller than B%, setting the index as a medium risk, and prompting field operators to pay attention to the change of the working condition of the shaft; when the index is larger than B%, setting the index as high risk, prompting field operators to start the pump for circulation, slowly lift and place the pump and continuously observe the pump.

12. The apparatus of claim 7, wherein the job scenario optimization module is specifically configured to:

drilling previewing is carried out according to the real-time data of the drilling occurrence state to obtain a drilling previewing result;

carrying out sensitivity analysis according to a drilling prediction result, determining bottom hole drilling pressure and torque parameters for avoiding drilling accident risks, and determining a shaft sticking risk index after completing shaft friction coefficient check;

and optimizing a drilling operation scheme according to the risk processing scheme corresponding to the drilling risk index.

13. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any of claims 1 to 6 when executing the computer program.

14. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when executed by a processor, implements the method of any one of claims 1 to 6.

15. A computer program product, characterized in that the computer program product comprises a computer program which, when being executed by a processor, carries out the method of any one of claims 1 to 6.

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