Onepetro

Gas hydrate plugging is considered a very challenging issue in offshore petroleum production and transportation. The phenomenon of hydrate plug formation involves low temperature and high pressure condition. Hydrates can damage equipment of petroleum transport system. In this study, a computational fluid dynamics (CFD) model is proposed to analyze the effect of hydrate flow in pipelines using ANSYS FLUENT multiphase flow modeling techniques. This study has been carried out with a joint industrial collaboration with GRi simulations, Canada. Two case studies have been investigated. The first one is with a pipeline with a dimension specified by an existing literature (Balakin et al., 2010a) for validating the simulation results. The other one is with a more complex geometry of M-shaped jumper including six elbows. Eulerian-Eulerian method was used to model the multiphase hydrate flow. Moreover, the population balance method (PBM) was used to model the hydrate agglomeration and breaking...

Objective: to obtain key phrases from OnePetro on "Digital Transformation" topic (petroleum context) and compare them with key phrases from Scopus (more general context). In Scopus, we try to limit context by technical topics, see Scopus query in the text below.  The purpose of such comparison is to find nonordinary items in general context which could be useful for petroleum context.

Emotional remark: I was deeply impressed when text mining of titles and abstracts from Scopus prompted the phrase "cyber-physical systems data analytics"  (Table 2) and then in dimensions.ai the query '"cyber-physical systems" AND analytic' suggested 31 publications in 2010 and 2030 in 2018!

Results: 

- "Cyber-physical systems data analytics" could be an  attractive emergence  topic for petroleum domain based on experience in other industries. Emphasis on analytics for cyber-physical systems.
- The concept of "platform" are important for both petroleum and common domains, in petroleum domain the  "IOT" term  is more frequent but  "analysis" is less frequent. The concept "cyber-physical systems data analytics" could incorporate both "IOT" and  "analysis".
- KH Coder 3 gives the most attractive results by extracting key phrases from titles and abstracts compare to VOSviewer and authors and KW+

References:

KH Coder (by HIGUCHI Koichi) is a free software for quantitative content analysis or text mining. It is also utilized for computational linguistics. https://khcoder.net/en/

Van Eck, N.J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. *Scientometrics*, *84*(2), 523-538.

Poor conformance is a major concern of Mangala, Bhagyam & Aishwarya (MBA) fields. The presence of high permeability streaks or thief layers between injection and production wells typically results in pre-mature water breakthrough, high water cut and deficient volumetric sweep. As a result, significant oil volumes in the reservoir may not be contacted by the injection fluid. Another concern is of low VRR (Voidage Replacement Ratio) in some of the layers due to reduced injectivity in those sands. Consequently, it has led to poor recovery from those sands. It is also a growing problem with the polymer deposition taking place in the wellbore particularly Mangala (undergoing full-field polymer flooding), leading to challenging wellbore cleanup operations. Several methods have been used in the past, both mechanical and chemical to improve the treatment fluids during stimulation. In this paper, we introduce a novel placement technique for Conformance Improvement which is practical, effecti...

Inflow Control Devices (ICDs) and their variants autonomous inflow control devices (AICDs) have been deployed in horizontal wells in the onshore asset for more than thirteen years. The technology was adopted for their utility to manage: well inflows, sweep efficiencies, pressure drops along the well trajectory and delay fluid breakthroughs. Also, they are adapted to partially isolate fractures and or high permeability streaks which might introduce abnormal flow conditions in the production system-if unchecked. Horizontal wells were favourable target application, due to the notorious "heel-to-toe-effect" replete in horizontal wells, which ICDs are typically designed to remedy. In the onshore asset, approximately fifty-one horizontal wells have been completed with ICDs or combination of ICDs-AICDs and some of them fully equipped for future open/close intervention capability using sliding side doors (SSDs). In this paper, a full assessment of ICDs design methodology and post ...

Nanoparticles (NPs) based techniques have shown great promises in all fields of science and industry. Nanofluid-flooding, as a replacement for water-flooding, has been suggested as an applicable application for enhanced oil recovery (EOR). The subsequent presence of these NPs and its potential aggregations in the porous media; however, can dramatically intensify the complexity of subsequent CO2 storage projects in the depleted hydrocarbon reservoir. Typically, CO2 from major emitters is injected into the low-productivity oil reservoir for storage and incremental oil recovery, as the last EOR stage. In this work, An extensive serious of experiments have been conducted using a high-pressure temperature vessel to apply a wide range of CO2-pressure (0.1 to 20 MPa), temperature (23 to 70 °C), and salinity (0 to 20wt% NaCl) during CO2/water interfacial tension (IFT) measurements. Moreover, to mimic all potential scenarios several nanofluids at different and NPs load were used. IFT of CO2/...

In an earlier paper, the authors conducted an analysis of the difference in acquisition and total ownership costs of steel and aluminum equivalent naval ship designs. It was shown that an aluminum ship can be built within just 7.5% of the acquisition cost of an equivalent steel ship. This is possible because of the cascading benefits of the aluminum ship’s significantly lighter weight. The aluminum ship was also shown to have operational and total ownership cost advantages. This paper reports on additional design effort conducted by the authors that validates the structural and fire insulation weight estimates used for both ship designs in the earlier paper.

Streamlines provide snapshots of flow patterns in the field, which simulation engineers can use to shorten the history match cycle when validating reservoir models. They can also help engineers develop injection strategies and improve the sweep efficiency by analyzing flow patterns and by estimating injector to producer relationships in the field during computations of various prediction scenarios. Our strategy in this study is to use details of reservoir conditions obtained by traditional reservoir simulations and calculate streamlines from the computed flow field. Saudi Aramco's in-house developed simulator POWERS and its post processing environment have been enhanced to generate streamlines from computed reservoir flow fields. A streamline tracing software developed at Texas A&M University and POWERS has been customized to generate streamline outputs. The algorithm used for computations is parallelized to run on Linux clusters. Several features, such as computations of inject...

In the petroleum industry, accurately predicting production potential of undrilled unconventional horizontal wells requires the use of highly complex models and is a constant research in progress. Deterministic approaches such as decline curve analysis (DCA) are used in most cases to estimate production potential due to ease of implementation. The main disadvantage of using DCA by itself is that it requires an existing well to forecast the production, which is very expensive to drill. This paper shows the procedures for building a flexible machine learning based decline curve-spatial method that can be easily used to predict the estimated ultimate recovery (EUR) of newly proposed wells without the requirement of costly data or other time consuming methods. A type of artificial neural network (ANN) called feed forward neural network (FFNN) was used as the machine learning method during this process. In order to achieve this goal, production and well data were collected from public domain sources. Power law exponential (PLE) DCA method was implemented on a portion of the existing wells with sufficient production history. The data then was divided into training and test sets. The training set was fed into the ANN model and the results were compared with the results obtained from other inherently spatial methods such as universal kriging, geographically weighted regression (GWR), and generalized additive model (GAM). Finally, the EUR of the new wells were compared to the original training and test data to observe any discrepancies in the prediction and necessary adjustments to the model hyperparameters were made when there were discrepancies. Analyzing and observing all the results from the various combinations of methods indicates that using ANN without any spatial correlation is a less reliable method to estimate the production potential of new wells in the Marcellus shale gas reservoir when compared to other inherently spatial methods. This study shows that it is necessary to include spatial correlations between wells in the EUR prediction of new wells in the ANN models. The predictive strength of other spatial methods were within a reasonable range. One of the main input parameters that may increase the accuracy of the model are completion parameters. However, most of these completion parameters that will affect the production are very difficult and expensive to obtain. These parameters which could not be included as inputs can increase the accuracy of these models when available. This experimental study indicates that there are many other possible variations of this method other than the methods discussed in this paper. It also shows that the spatial correlation of wells is highly important when predicting the new well production in unconventional reservoirs. This is a flexible method, which can be easily modified to find better predictive methods for other areas of interest.

Summary The nonparametric transformation is a data-driven technique, which can be used to estimate optimal correlations between a dependent variable (response) and a set of independent parameters (predictors). This study introduces a systematic methodology using the nonparametric transformation concept and the alternating conditional expectation (ACE) algorithm to estimate the effective gas permeability using conventional logs and the core data. The ACE algorithm was employed in the current work using the MATLAB® (The MathWorks, Inc., Natick, Massachusetts, USA) code and the open-source GRaphical ACE (GRACE) software (Xue et al. 1997) for deriving the optimal nonparametric correlations for predicting the permeability. The methodology was applied to a heterogeneous formation [Bahariya (BAH)] in Egypt to understand its characteristics and predict its permeability more accurately. The BAH Formation is considered one of the main sources for oil production throughout the Western Desert (...

Conventional slick-line temperature surveys enable successive temperature measurements at pre-determined depth stations along the well-bore. This method has two major drawbacks. The wellbore fluid flow dynamics impact the temperature accuracy while the uncertainty in depth leads to erroneous conclusions on spatial temperature distribution along the wellbore. Remedial actions based on these temperature measurements do not always help optimize productivity or injectivity. To overcome these measurement uncertainties and correctly evaluate the gas-lift system performance for the oil producer wells or to identify temperatures anomalies, such as flow behind casing for water injection wells, continuous temperature measurements with time and depth are needed. The slick-line fiber optics distributed temperature sensors technology presented in this paper measure simultaneous temperature traces along the well-bore with time. This is widely used in oil wells located at Maracaibo Lake, where app...

This work has been carried out to model and simulate a typical acid gas absorption process using Aspen HYSYS process simulator. The chemical components involved in the process development were water, methane, ethane, propane, higher alkanes, carbon dioxide, hydrogen sulphide, nitrogen and amines: monoethanolamine (MEA), diethanolamine (DEA), triethanolamine (TEA) and methyldiethanolamine (MDEA). The fluid package selected for the simulation before entering the simulation environment was Acid Gas – Chemical Solvents. In the simulation environment, the model was developed by picking an absorber from the Model Palette, placing it and assigning the input and the output streams involved before inputting the parameters required for model convergence. The carbon dioxide-rich feed gas was made to enter the absorber at the bottom inlet stream while the lean amine stream entered at the top inlet and showered down on the uprising gas thereby trapping the carbon dioxide molecules within the gas...

In the petroleum industry, accurately predicting production potential of undrilled unconventional horizontal wells requires the use of highly complex models and is a constant research in progress. Deterministic approaches such as decline curve analysis (DCA) are used in most cases to estimate production potential due to ease of implementation. The main disadvantage of using DCA by itself is that it requires an existing well to forecast the production, which is very expensive to drill. This paper shows the procedures for building a flexible machine learning based decline curve-spatial method that can be easily used to predict the estimated ultimate recovery (EUR) of newly proposed wells without the requirement of costly data or other time consuming methods. A type of artificial neural network (ANN) called feed forward neural network (FFNN) was used as the machine learning method during this process. In order to achieve this goal, production and well data were collected from public domain sources. Power law exponential (PLE) DCA method was implemented on a portion of the existing wells with sufficient production history. The data then was divided into training and test sets. The training set was fed into the ANN model and the results were compared with the results obtained from other inherently spatial methods such as universal kriging, geographically weighted regression (GWR), and generalized additive model (GAM). Finally, the EUR of the new wells were compared to the original training and test data to observe any discrepancies in the prediction and necessary adjustments to the model hyperparameters were made when there were discrepancies. Analyzing and observing all the results from the various combinations of methods indicates that using ANN without any spatial correlation is a less reliable method to estimate the production potential of new wells in the Marcellus shale gas reservoir when compared to other inherently spatial methods. This study shows that it is necessary to include spatial correlations between wells in the EUR prediction of new wells in the ANN models. The predictive strength of other spatial methods were within a reasonable range. One of the main input parameters that may increase the accuracy of the model are completion parameters. However, most of these completion parameters that will affect the production are very difficult and expensive to obtain. These parameters which could not be included as inputs can increase the accuracy of these models when available. This experimental study indicates that there are many other possible variations of this method other than the methods discussed in this paper. It also shows that the spatial correlation of wells is highly important when predicting the new well production in unconventional reservoirs. This is a flexible method, which can be easily modified to find better predictive methods for other areas of interest.

The petroleum industry is currently being faced with a growing number of ageing offshore platforms that are no longer in use and require to be decommissioned. Offshore decommissioning is a complex venture, and such projects are expected to cost the industry billions of dollars in the next two decades. Early knowledge of decommissioning cost is important to platform owners who bear the asset retirement obligation. However, obtaining the cost estimate for decommissioning an offshore platform is a challenging task that requires extensive structural and economic studies. This is further complicated by the existence of several decommissioning options such as complete and partial removal. In this paper, project costs for decommissioning 23 offshore platforms under three different scenarios are estimated using information from a publicly available source which only specified the costs of completely removing the platforms. A novel mathematical model for predicting the decommissioning cost f...

The PEP structure in Matindok block in Central Sulawesi has been proven to produce gas reserves in the Minahaki formation based on the first exploration well PEP-001 that was drilled in 2018. The PEP structure has a Miocene carbonate build-up play, and the target reservoir is the M member pinnacle carbonate reef. One of the main challenges in this area is low resolution of seismic data, leading to a high depth uncertainty of top M position. The PEP-001 well was planned to set the 9 ⅝-in casing point above top M. Offset wells did not show any clear markers in the thick shale above M formation, that could have been used for log correlation. In previously drilled offset wells correlation was done conventionally by taking cutting samples and relying on drilling parameters break. However, when PEP-001 was drilled, no apparent drilling break was observed. By the time cuttings reached surface, the bit had drilled into 20-m thickness of M formation. Since casing covered most part of the upp...

This paper presents a new method for forecasting post-fracturing responses in a tight oil reservoir using historical hydraulic fracturing data. The methodology is based on a nonlinear regression method called Variable Structure Regression (VSR). Data for 80 frac jobs were used to calibrate and predict responses. Information per fracturing job included feet of perforation, number of perforations per stage, number of stages, pad volume, slurry volume and sand volume. Information for a set of hydraulically fractured vertical wells was used to test the proposed technique. The VSR method establishes the optimal nonlinear dependencies of variables to predict the cumulative liquid production after fracturing. This method determines the relationships between fracturing parameters and post-fracturing productions in the form of linguistic terms, thereby providing a physical understanding of the process. The exact mathematical structure of these linguistic terms and the number of terms are est...