A. Gimazov, Anzhelika Igorevna Balionis, E. Sergeev, Elmir Rovshanovich Khudiev, R. Uchuev
To create a technology for selection the optimal RPM method the simulation on a sector hydrodynamic model of the field has performed. Different injection modes (continuous injection, alternating, cyclic), injection agents and completions of injection wells were tried during the modeling. The key factors, which influence the choice of the RPM method, were determined. Pilot industrial works include short-term nitrogen injection, long-term APG injection, and production from pilot wells in various modes. Well research include pressure testing, well testing after gas injection, recording of inflow profiles, laboratory studies of the Priobskoye field's own core. Evaluation of the potential of gas enhanced oil recovery methods shows their significantly higher efficiency compared to stationary waterflooding. The suggested approach can minimize the risks in the transition to previously untested development methods and methods of enhanced oil recovery in ultra-low-permeability reservoirs of the Achimov deposits. The analysis and the results of partially conducted pilot projects (at the moment) have showed a high potential for gas injection in certain areas of the field.
{"title":"Selection of EOR Technology in Ultra-Low-Permeability Reservoirs of the Achimov Deposits of the Priobsky Field","authors":"A. Gimazov, Anzhelika Igorevna Balionis, E. Sergeev, Elmir Rovshanovich Khudiev, R. Uchuev","doi":"10.2118/206401-ms","DOIUrl":"https://doi.org/10.2118/206401-ms","url":null,"abstract":"\u0000 To create a technology for selection the optimal RPM method the simulation on a sector hydrodynamic model of the field has performed. Different injection modes (continuous injection, alternating, cyclic), injection agents and completions of injection wells were tried during the modeling. The key factors, which influence the choice of the RPM method, were determined. Pilot industrial works include short-term nitrogen injection, long-term APG injection, and production from pilot wells in various modes. Well research include pressure testing, well testing after gas injection, recording of inflow profiles, laboratory studies of the Priobskoye field's own core. Evaluation of the potential of gas enhanced oil recovery methods shows their significantly higher efficiency compared to stationary waterflooding. The suggested approach can minimize the risks in the transition to previously untested development methods and methods of enhanced oil recovery in ultra-low-permeability reservoirs of the Achimov deposits. The analysis and the results of partially conducted pilot projects (at the moment) have showed a high potential for gas injection in certain areas of the field.","PeriodicalId":11017,"journal":{"name":"Day 2 Wed, October 13, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88361317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pavel Vladimirovich Markov, A. V. Gorshkov, Sergey Vladimirovich Shadrin
The paper presents a complex approach based on the experience of the authors of this article for creating and maintaining integrated asset models (IAM) and implementing a digital data management platform. Problems of using IAM for the operational management of field development and production are that the data is not accurate, the measurements are spaced in time, and there is not enough data to understand the physical phenomena taking place. The complex approach is that to provide integrated asset models with high-quality data, it is necessary to build new processes, create new specialties and competencies, the key success factor is the combination of the experience of Customer (oil company), Internal oil-related service of Customer (geological and geophysical research), External contractor of oil-related service (the combination of experience in geological and geophysical research, experience in integrated asset modeling and operational support for field development using integrated asset modeling tools and digitalization of data management). The best way to implement the approach of creating joint Integrated Team of External and Internal oilfield service Contractors in the form of Complex Service Engineering Center, the task for which which was the organization of a cyber-physical system for collecting field data, verifying data, identifying problem areas in data, defining approaches to eliminating problem areas using tools of automation tools for working with data, the flexible management of well testing and survey programs, the operational formation of well testing and survey design for non-standard situations. Particular attention in this complex approach is paid to working with initial field data, this article provides a general scheme for verifying the various parameters of well operation and an example of its use for flow rates, as well as examples of the quality analysis of reservoir pressures based on the use of a two-dimensional one-phase proxy reservoir model and the quality analysis of GOR for a well. Based on the developed complex approach, the paper provides examples of strategic and operational problems for a field - the assessment of optimal production for a field and the assessment of oil shortfalls for a well, respectively.
{"title":"Complex Approach to Creation and Maintenance of Integrated Asset Models and Implementation of Digital Data Management Platform","authors":"Pavel Vladimirovich Markov, A. V. Gorshkov, Sergey Vladimirovich Shadrin","doi":"10.2118/206536-ms","DOIUrl":"https://doi.org/10.2118/206536-ms","url":null,"abstract":"\u0000 The paper presents a complex approach based on the experience of the authors of this article for creating and maintaining integrated asset models (IAM) and implementing a digital data management platform. Problems of using IAM for the operational management of field development and production are that the data is not accurate, the measurements are spaced in time, and there is not enough data to understand the physical phenomena taking place. The complex approach is that to provide integrated asset models with high-quality data, it is necessary to build new processes, create new specialties and competencies, the key success factor is the combination of the experience of Customer (oil company), Internal oil-related service of Customer (geological and geophysical research), External contractor of oil-related service (the combination of experience in geological and geophysical research, experience in integrated asset modeling and operational support for field development using integrated asset modeling tools and digitalization of data management). The best way to implement the approach of creating joint Integrated Team of External and Internal oilfield service Contractors in the form of Complex Service Engineering Center, the task for which which was the organization of a cyber-physical system for collecting field data, verifying data, identifying problem areas in data, defining approaches to eliminating problem areas using tools of automation tools for working with data, the flexible management of well testing and survey programs, the operational formation of well testing and survey design for non-standard situations. Particular attention in this complex approach is paid to working with initial field data, this article provides a general scheme for verifying the various parameters of well operation and an example of its use for flow rates, as well as examples of the quality analysis of reservoir pressures based on the use of a two-dimensional one-phase proxy reservoir model and the quality analysis of GOR for a well. Based on the developed complex approach, the paper provides examples of strategic and operational problems for a field - the assessment of optimal production for a field and the assessment of oil shortfalls for a well, respectively.","PeriodicalId":11017,"journal":{"name":"Day 2 Wed, October 13, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75379541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. A. Isaev, R. Takhautdinov, V. I. Malykhin, A. A. Sharifullin
This paper presents a set of activities to reduce water cut and develop a technical solution to measure water cut: measurement of watercut, flow rates and gas-oil ratio of a well output using a mobile unit. tracer tests and conformance control operations - watercut of reacting wells within Bashkirian stage decreased by 16,6% after those operations were performed. water flow control, flow deviation and remedying production casing damages made it possible to reduce extraction of produced water and, accordingly, the cost of oil production. development of Liquid Phase Separation Device enabled alternate delivery of oil and water to the intake of downhole pump.
{"title":"A Set of Solutions to Reduce the Water Cut in Well Production","authors":"A. A. Isaev, R. Takhautdinov, V. I. Malykhin, A. A. Sharifullin","doi":"10.2118/206462-ms","DOIUrl":"https://doi.org/10.2118/206462-ms","url":null,"abstract":"\u0000 This paper presents a set of activities to reduce water cut and develop a technical solution to measure water cut:\u0000 measurement of watercut, flow rates and gas-oil ratio of a well output using a mobile unit. tracer tests and conformance control operations - watercut of reacting wells within Bashkirian stage decreased by 16,6% after those operations were performed. water flow control, flow deviation and remedying production casing damages made it possible to reduce extraction of produced water and, accordingly, the cost of oil production. development of Liquid Phase Separation Device enabled alternate delivery of oil and water to the intake of downhole pump.","PeriodicalId":11017,"journal":{"name":"Day 2 Wed, October 13, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73745532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Valery Sorokin, Alexey Semenovich Gudoshnikov, Denis Vyacheslavovich Nyunyaykin, Andrey Anatolyevich Kochenkov, P. Sethuraman, Sabina Barysheva, D. S. Lipanin, A.A. Mokrev, Sergey Aleksandrovich Vukolov, A.A. Ardalin
This paper describes a production optimiser Pilot, developed by Rosneft/Samotlorneftegaz, with support from bp and deployed in JSC Samotlorneftegaz - a vast, mature, water-flooded, high water-cut and artificially-lifted oil field. Objectives include creating a digital twin for a sub-system of 600 wells and ~180 km of pipeline network, applying discrete, continuous and constrained optimisation techniques to maximise production, developing sustainable deployment workflows, implementing optimiser recommendations in the field and tracking incremental value realisation. This proof-of-concept Pilot and field trial approach was adopted to understand the optimisation technology capability and work-flow sustainability, prior to a field-wide roll-out. The periodic optimisation activity workflows include the creation of a "Digital Twin", a validated surface infrastructure model that is fully calibrated to mimic field performance, followed by performing optimisation that includes all the relevant constraints. Optimisation was trialled using two different classes of algorithms – based on sequential-modular and equation-oriented techniques. This strategy minimises optimisation failure risks and highlights potential performance issues for such large-scale systems. Optimiser recommendations were consolidated, field-implemented and values tracked. The optimiser Pilot development was undertaken during the fourth quarter of 2019. The delivered minimum viable product and workflows were used for field trials during 2019-20 and continuously improved based on the learnings. Specialists from both bp and Rosneft, along with three consulting organisations (1 in Russia and 2 in the UK) collaborated and worked as one-team to deliver the Pilot. Optimiser recommendations for maximising production include continuous and discrete decisions such as ESP frequency changes, high water-cut well shut-ins and prioritised ESP lists for installing variable speed drives. Field production increase of 1% was achieved in 2020 and tracked. Enduring capabilities were built, and sustainable work-flows developed. Field-wide optimisation for Samotlorneftegaz is non-trivial due to the sheer size, with over 9,000 active wells and due to continuously transient operations arising from frequent well-work, well shut-in's, new well delivery, pipeline modifications and cyclic mode of operations in some wells. This Pilot has provided assurance for the optimisation technical feasibility and workflow sustainability. A second Pilot of similar complexity but with different pressure-flow system response is planned. The combined results will help to decide about the full-field roll-out for this vast field, which is anticipated to deliver around 1% of additional production. This Pilot has demonstrated the applicability of discrete and continuous variable constrained optimisation techniques to large-scale production networks, with very high well-count. Furthermore, the developed workflows for configuring an
{"title":"Production Optimiser Pilot for the Large Artificially-Lifted and Mature Samotlor Oil Field","authors":"Valery Sorokin, Alexey Semenovich Gudoshnikov, Denis Vyacheslavovich Nyunyaykin, Andrey Anatolyevich Kochenkov, P. Sethuraman, Sabina Barysheva, D. S. Lipanin, A.A. Mokrev, Sergey Aleksandrovich Vukolov, A.A. Ardalin","doi":"10.2118/206517-ms","DOIUrl":"https://doi.org/10.2118/206517-ms","url":null,"abstract":"\u0000 This paper describes a production optimiser Pilot, developed by Rosneft/Samotlorneftegaz, with support from bp and deployed in JSC Samotlorneftegaz - a vast, mature, water-flooded, high water-cut and artificially-lifted oil field. Objectives include creating a digital twin for a sub-system of 600 wells and ~180 km of pipeline network, applying discrete, continuous and constrained optimisation techniques to maximise production, developing sustainable deployment workflows, implementing optimiser recommendations in the field and tracking incremental value realisation. This proof-of-concept Pilot and field trial approach was adopted to understand the optimisation technology capability and work-flow sustainability, prior to a field-wide roll-out. The periodic optimisation activity workflows include the creation of a \"Digital Twin\", a validated surface infrastructure model that is fully calibrated to mimic field performance, followed by performing optimisation that includes all the relevant constraints. Optimisation was trialled using two different classes of algorithms – based on sequential-modular and equation-oriented techniques. This strategy minimises optimisation failure risks and highlights potential performance issues for such large-scale systems. Optimiser recommendations were consolidated, field-implemented and values tracked.\u0000 The optimiser Pilot development was undertaken during the fourth quarter of 2019. The delivered minimum viable product and workflows were used for field trials during 2019-20 and continuously improved based on the learnings. Specialists from both bp and Rosneft, along with three consulting organisations (1 in Russia and 2 in the UK) collaborated and worked as one-team to deliver the Pilot. Optimiser recommendations for maximising production include continuous and discrete decisions such as ESP frequency changes, high water-cut well shut-ins and prioritised ESP lists for installing variable speed drives. Field production increase of 1% was achieved in 2020 and tracked. Enduring capabilities were built, and sustainable work-flows developed.\u0000 Field-wide optimisation for Samotlorneftegaz is non-trivial due to the sheer size, with over 9,000 active wells and due to continuously transient operations arising from frequent well-work, well shut-in's, new well delivery, pipeline modifications and cyclic mode of operations in some wells. This Pilot has provided assurance for the optimisation technical feasibility and workflow sustainability. A second Pilot of similar complexity but with different pressure-flow system response is planned. The combined results will help to decide about the full-field roll-out for this vast field, which is anticipated to deliver around 1% of additional production.\u0000 This Pilot has demonstrated the applicability of discrete and continuous variable constrained optimisation techniques to large-scale production networks, with very high well-count. Furthermore, the developed workflows for configuring an","PeriodicalId":11017,"journal":{"name":"Day 2 Wed, October 13, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73861185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rushad Ravilievich Rakhimov, O. Zhdaneev, K. Frolov, Maxim Pavlovich Babich
The ultimate objective of this paper is to describe the experience of using a machine learning model prepared by the ensemble method to prevent stuck pipe events during well construction process on extended reach wells. The tasks performed include collecting, analyzing and cleaning historical data, selecting and preparing a machine learning model, testing it on real-time data by means of desktop application. The idea is to display the solution at the rig floor, allowing Driller to quickly take actions for prevention of stuck pipe event. Historical data mining and analysis were performed using software for remote monitoring. Preparation, labelling and cleaning of historical and real-time data were executed using programmable scripts and big data techniques. The machine learning algorithm was developed using the ensemble method, which allows to combine several models to improve the final result. On the field of interest, the most common type of stuck pipe are solids induced pack offs. They occur due to insufficient hole cleaning from drilled cuttings and wellbore collapse due to rocks instability. Stuck pipe prevention on extended reach drilling (ERD) wells requires holistic approach meanwhile final role is assigned to the driller. Due to continuously exceeding ERD envelope and increased workloads on both personnel and drilling equipment, the effectiveness of preventing accidents is deteriorating. This leads to severe consequences: Bottom Hole Assembly lost in hole, the necessity to re-drill the bore and eventually to increased Non-Productive Time (NPT). Developed application based on ensemble machine learning algorithm shows prediction accuracy above 94%. Reacting on alarms, driller can quickly take measures to prevent downhole accidents during well construction of ERD wells.
{"title":"Stuck Pipe Early Detection on Extended Reach Wells Using Ensemble Method of Machine Learning","authors":"Rushad Ravilievich Rakhimov, O. Zhdaneev, K. Frolov, Maxim Pavlovich Babich","doi":"10.2118/206516-ms","DOIUrl":"https://doi.org/10.2118/206516-ms","url":null,"abstract":"\u0000 The ultimate objective of this paper is to describe the experience of using a machine learning model prepared by the ensemble method to prevent stuck pipe events during well construction process on extended reach wells. The tasks performed include collecting, analyzing and cleaning historical data, selecting and preparing a machine learning model, testing it on real-time data by means of desktop application. The idea is to display the solution at the rig floor, allowing Driller to quickly take actions for prevention of stuck pipe event.\u0000 Historical data mining and analysis were performed using software for remote monitoring. Preparation, labelling and cleaning of historical and real-time data were executed using programmable scripts and big data techniques. The machine learning algorithm was developed using the ensemble method, which allows to combine several models to improve the final result.\u0000 On the field of interest, the most common type of stuck pipe are solids induced pack offs. They occur due to insufficient hole cleaning from drilled cuttings and wellbore collapse due to rocks instability. Stuck pipe prevention on extended reach drilling (ERD) wells requires holistic approach meanwhile final role is assigned to the driller. Due to continuously exceeding ERD envelope and increased workloads on both personnel and drilling equipment, the effectiveness of preventing accidents is deteriorating. This leads to severe consequences: Bottom Hole Assembly lost in hole, the necessity to re-drill the bore and eventually to increased Non-Productive Time (NPT).\u0000 Developed application based on ensemble machine learning algorithm shows prediction accuracy above 94%. Reacting on alarms, driller can quickly take measures to prevent downhole accidents during well construction of ERD wells.","PeriodicalId":11017,"journal":{"name":"Day 2 Wed, October 13, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85261522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The paper presents the results of a pilot project implementing WAG injection at the oilfield with carbonate reservoir, characterized by low efficiency of traditional waterflooding. The objective of the pilot project was to evaluate the efficiency of this enhanced oil recovery method for conditions of the specific oil field. For the initial introduction of WAG, an area of the reservoir with minimal potential risks has been identified. During the test injections of water and gas, production parameters were monitored, including the oil production rates of the reacting wells and the water and gas injection rates of injection wells, the change in the density and composition of the produced fluids. With first positive results, the pilot area of the reservoir was expanded. In accordance with the responses of the producing wells to the injection of displacing agents, the injection rates were adjusted, and the production intensified, with the aim of maximizing the effect of WAG. The results obtained in practice were reproduced in the simulation model sector in order to obtain a project curve characterizing an increase in oil recovery due to water-alternating gas injection. Practical results obtained during pilot testing of the technology show that the injection of gas and water alternately can reduce the water cut of the reacting wells and increase overall oil production, providing more efficient displacement compared to traditional waterflooding. The use of WAG after the waterflooding provides an increase in oil recovery and a decrease in residual oil saturation. The water cut of the produced liquid decreased from 98% to 80%, an increase in oil production rate of 100 tons/day was obtained. The increase in the oil recovery factor is estimated at approximately 7.5% at gas injection of 1.5 hydrocarbon pore volumes. Based on the received results, the displacement characteristic was constructed. Methods for monitoring the effectiveness of WAG have been determined, and studies are planned to be carried out when designing a full-scale WAG project at the field. This project is the first pilot project in Russia implementing WAG injection in a field with a carbonate reservoir. During the pilot project, the technical feasibility of implementing this EOR method was confirmed, as well as its efficiency in terms of increasing the oil recovery factor for the conditions of the carbonate reservoir of Eastern Siberia, characterized by high water cut and low values of oil displacement coefficients during waterflooding.
{"title":"Pilot Project Evaluating WAG Efficiency for Carbonate Reservoir in Eastern Siberia","authors":"V. Zharko, D. Burdakov","doi":"10.2118/206417-ms","DOIUrl":"https://doi.org/10.2118/206417-ms","url":null,"abstract":"\u0000 The paper presents the results of a pilot project implementing WAG injection at the oilfield with carbonate reservoir, characterized by low efficiency of traditional waterflooding. The objective of the pilot project was to evaluate the efficiency of this enhanced oil recovery method for conditions of the specific oil field.\u0000 For the initial introduction of WAG, an area of the reservoir with minimal potential risks has been identified. During the test injections of water and gas, production parameters were monitored, including the oil production rates of the reacting wells and the water and gas injection rates of injection wells, the change in the density and composition of the produced fluids. With first positive results, the pilot area of the reservoir was expanded. In accordance with the responses of the producing wells to the injection of displacing agents, the injection rates were adjusted, and the production intensified, with the aim of maximizing the effect of WAG. The results obtained in practice were reproduced in the simulation model sector in order to obtain a project curve characterizing an increase in oil recovery due to water-alternating gas injection.\u0000 Practical results obtained during pilot testing of the technology show that the injection of gas and water alternately can reduce the water cut of the reacting wells and increase overall oil production, providing more efficient displacement compared to traditional waterflooding. The use of WAG after the waterflooding provides an increase in oil recovery and a decrease in residual oil saturation. The water cut of the produced liquid decreased from 98% to 80%, an increase in oil production rate of 100 tons/day was obtained. The increase in the oil recovery factor is estimated at approximately 7.5% at gas injection of 1.5 hydrocarbon pore volumes. Based on the received results, the displacement characteristic was constructed. Methods for monitoring the effectiveness of WAG have been determined, and studies are planned to be carried out when designing a full-scale WAG project at the field.\u0000 This project is the first pilot project in Russia implementing WAG injection in a field with a carbonate reservoir. During the pilot project, the technical feasibility of implementing this EOR method was confirmed, as well as its efficiency in terms of increasing the oil recovery factor for the conditions of the carbonate reservoir of Eastern Siberia, characterized by high water cut and low values of oil displacement coefficients during waterflooding.","PeriodicalId":11017,"journal":{"name":"Day 2 Wed, October 13, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79751503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xiaoxiao Li, X. Yue, Jirui Zou, Li-juan Zhang, K. Tang
In this study, a visualized physical model of artificial oil film was firstly designed to investigate the oil film displacement mechanisms. Numerous comparative experiments were conducted to explore the detachment mechanisms of oil film and oil recovery performances in different fluid mediums with flow rate. In addition, the of influencing factors of oil film were comprehensively evaluated, which mainly includes: flow rate, surfactant behaviors, and crude oil viscosity. The results show that, (1) regardless of the viscosity of crude oil, flow rate presents a limited contribution to the detachment of oil film and the maximum of ultimate oil film displacement efficiency is only approximately 10%; (2) surfactant flooding has a synergistic effect on the oil film displacement on two aspects of interfacial tension (ITF) reduction and emulsifying capacity. Giving the most outstanding performance for two oil samples in all runs, IFT reduction of ultra-low value is not the only decisive factor affecting oil film displacement efficiency, but the emulsifying capability plays the key role to the detachment of oil film due to effect of emulsifying and dispersing on oil film; (3) the increasing flow rate of surfactant flooding is able to enhance the detachment of oil film but has an objective effect on the final oil film displacement efficiency; (4) flow rate have the much influence on the detachment of oil film, but the most easily controlled factor is the surfactant property. The finding provides basis for oil film detachment and surfactant selection EOR application.
{"title":"The Role of Emulsification and Interfacial Tension Ift For the Enhanced Oil Recovery Eor in Surfactant Flooding","authors":"Xiaoxiao Li, X. Yue, Jirui Zou, Li-juan Zhang, K. Tang","doi":"10.2118/206432-ms","DOIUrl":"https://doi.org/10.2118/206432-ms","url":null,"abstract":"\u0000 In this study, a visualized physical model of artificial oil film was firstly designed to investigate the oil film displacement mechanisms. Numerous comparative experiments were conducted to explore the detachment mechanisms of oil film and oil recovery performances in different fluid mediums with flow rate. In addition, the of influencing factors of oil film were comprehensively evaluated, which mainly includes: flow rate, surfactant behaviors, and crude oil viscosity.\u0000 The results show that, (1) regardless of the viscosity of crude oil, flow rate presents a limited contribution to the detachment of oil film and the maximum of ultimate oil film displacement efficiency is only approximately 10%; (2) surfactant flooding has a synergistic effect on the oil film displacement on two aspects of interfacial tension (ITF) reduction and emulsifying capacity. Giving the most outstanding performance for two oil samples in all runs, IFT reduction of ultra-low value is not the only decisive factor affecting oil film displacement efficiency, but the emulsifying capability plays the key role to the detachment of oil film due to effect of emulsifying and dispersing on oil film; (3) the increasing flow rate of surfactant flooding is able to enhance the detachment of oil film but has an objective effect on the final oil film displacement efficiency; (4) flow rate have the much influence on the detachment of oil film, but the most easily controlled factor is the surfactant property. The finding provides basis for oil film detachment and surfactant selection EOR application.","PeriodicalId":11017,"journal":{"name":"Day 2 Wed, October 13, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84098369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alexey Vasilievich Timonov, A. R. Shabonas, Sergey Alexandrovich Schmidt
The main technology used to optimize field development is hydrodynamic modeling, which is very costly in terms of computing resources and expert time to configure the model. And in the case of brownfields, the complexity increases exponentially. The paper describes the stages of developing a hybrid geological-physical-mathematical proxy model using machine learning methods, which allows performing multivariate calculations and predicting production including various injection well operating regimes. Based on the calculations, we search for the optimal ratio of injection volume distribution to injection wells under given infrastructural constraints. The approach implemented in this work takes into account many factors (some features of the geological structure, history of field development, mutual influence of wells, etc.) and can offer optimal options for distribution of injection volumes of injection wells without performing full-scale or sector hydrodynamic simulation. To predict production, we use machine learning methods (based on decision trees and neural networks) and methods for optimizing the target functions. As a result of this research, a unified algorithm for data verification and preprocessing has been developed for feature extraction tasks and the use of deep machine learning models as input data. Various machine learning algorithms were tested and it was determined that the highest prediction accuracy is achieved by building machine learning models based on Temporal Convolutional Networks (TCN) and gradient boosting. Developed and tested an algorithm for finding the optimal allocation of injection volumes, taking into account the existing infrastructure constraints. Different optimization algorithms are tested. It is determined that the choice and setting of boundary conditions is critical for optimization algorithms in this problem. An integrated approach was tested on terrigenous formations of the West Siberian field, where the developed algorithm showed effectiveness.
{"title":"Field Development Optimization Using Machine Learning Methods to Identify the Optimal Water Flooding Regime","authors":"Alexey Vasilievich Timonov, A. R. Shabonas, Sergey Alexandrovich Schmidt","doi":"10.2118/206533-ms","DOIUrl":"https://doi.org/10.2118/206533-ms","url":null,"abstract":"\u0000 The main technology used to optimize field development is hydrodynamic modeling, which is very costly in terms of computing resources and expert time to configure the model. And in the case of brownfields, the complexity increases exponentially.\u0000 The paper describes the stages of developing a hybrid geological-physical-mathematical proxy model using machine learning methods, which allows performing multivariate calculations and predicting production including various injection well operating regimes. Based on the calculations, we search for the optimal ratio of injection volume distribution to injection wells under given infrastructural constraints.\u0000 The approach implemented in this work takes into account many factors (some features of the geological structure, history of field development, mutual influence of wells, etc.) and can offer optimal options for distribution of injection volumes of injection wells without performing full-scale or sector hydrodynamic simulation.\u0000 To predict production, we use machine learning methods (based on decision trees and neural networks) and methods for optimizing the target functions.\u0000 As a result of this research, a unified algorithm for data verification and preprocessing has been developed for feature extraction tasks and the use of deep machine learning models as input data.\u0000 Various machine learning algorithms were tested and it was determined that the highest prediction accuracy is achieved by building machine learning models based on Temporal Convolutional Networks (TCN) and gradient boosting.\u0000 Developed and tested an algorithm for finding the optimal allocation of injection volumes, taking into account the existing infrastructure constraints. Different optimization algorithms are tested. It is determined that the choice and setting of boundary conditions is critical for optimization algorithms in this problem.\u0000 An integrated approach was tested on terrigenous formations of the West Siberian field, where the developed algorithm showed effectiveness.","PeriodicalId":11017,"journal":{"name":"Day 2 Wed, October 13, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74310934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Arsenii Stanislavovich Posdyshev, P. Shelyakin, Nurislam Shaikhutdinov, A. A. Popov, M. Logacheva, M. Tutukina, M. Gelfand
The purpose of this work is to adapt and apply Next Generation Sequencing methods in oil and gas well field studies. Relatively recent NGS methods provide a description of a geological formation by analyzing millions of DNA sequences and represent an entirely new way to obtain information about oil and gas reservoirs and the composition of their fluids, which could significantly change the approach to exploration and field development. We present the results of pilot work to determine the inflow profile in a horizontal well based on DNA markers. The technology is based on the comparison of bacterial DNA from drill cuttings obtained while drilling with DNA from microorganisms of fluids obtained during production at the wellhead. Because of their high selectivity, individual microbes live only under certain conditions (salinity, oil saturation, temperature) and can be used as unique natural biomarkers. The comparison of DNA samples of drilling cutting and produced fluid allows for identification of the segment of the horizontal well from which the main flow comes, as well as identifying the type of incoming fluid (water, oil, gas) without stopping the operation process and without conducting expensive downhole operations. As a result of these studies, the microbial communities of the oil-bearing sands and formation fluids of the Cretaceous deposits (group BS) in Western Siberia were identified, and the relative numerical ratio of microorganisms in the formations was determined. It was shown that the microbiome diversity changes with depth, and depends on the lithological composition, and sequencing data obtained from cuttings samples correlate with data from wellhead samples of produced fluid. Thus, the practical applicability of DNA sequencing for solving field problems in oil and gas field development, in particular for determining the inflow profile in horizontal wells, was confirmed.
{"title":"Using DNA-Logging to Determine Inflow Profile in Horizontal Wells","authors":"Arsenii Stanislavovich Posdyshev, P. Shelyakin, Nurislam Shaikhutdinov, A. A. Popov, M. Logacheva, M. Tutukina, M. Gelfand","doi":"10.2118/206515-ms","DOIUrl":"https://doi.org/10.2118/206515-ms","url":null,"abstract":"\u0000 The purpose of this work is to adapt and apply Next Generation Sequencing methods in oil and gas well field studies. Relatively recent NGS methods provide a description of a geological formation by analyzing millions of DNA sequences and represent an entirely new way to obtain information about oil and gas reservoirs and the composition of their fluids, which could significantly change the approach to exploration and field development.\u0000 We present the results of pilot work to determine the inflow profile in a horizontal well based on DNA markers. The technology is based on the comparison of bacterial DNA from drill cuttings obtained while drilling with DNA from microorganisms of fluids obtained during production at the wellhead. Because of their high selectivity, individual microbes live only under certain conditions (salinity, oil saturation, temperature) and can be used as unique natural biomarkers. The comparison of DNA samples of drilling cutting and produced fluid allows for identification of the segment of the horizontal well from which the main flow comes, as well as identifying the type of incoming fluid (water, oil, gas) without stopping the operation process and without conducting expensive downhole operations.\u0000 As a result of these studies, the microbial communities of the oil-bearing sands and formation fluids of the Cretaceous deposits (group BS) in Western Siberia were identified, and the relative numerical ratio of microorganisms in the formations was determined. It was shown that the microbiome diversity changes with depth, and depends on the lithological composition, and sequencing data obtained from cuttings samples correlate with data from wellhead samples of produced fluid. Thus, the practical applicability of DNA sequencing for solving field problems in oil and gas field development, in particular for determining the inflow profile in horizontal wells, was confirmed.","PeriodicalId":11017,"journal":{"name":"Day 2 Wed, October 13, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74323844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Y. Trushin, A. Aleshchenko, O. Zoshchenko, M. Arsamakov, I. Tkachev, D. S. Kruglov, A. Kornilov, D. Batrshin
The paper considers the use of a surfactant-polymer composition for the mobilization of light paraffinic oil from the D3-III carbonate reservoir at a reservoir temperature of 62°C, as well as the results of its tests in field conditions. Earlier, the composition showed its effectiveness on model carbonate cores with salinity from current (50-80 g/l) to reservoir (up to 170 g/l), in the presence of surfactants, type III microemulsions according to Winsor with oil were obtained. Based on the results of the filtration experiments performed on our own core from the productive formation D3-III, an increase in the displacement efficiency of surfactant-polymer compositions compared to water was obtained 11–14% (with a total surfactant concentration of 1%), irreversible surfactant losses in water-saturated rock–up to 0, 38 mg/g. Displacement efficiency after water and surfactant-polymer composition flooding was also estimated in the field conditions using SWCTT; its results were interpreted by various methods (analytical, in a hydrodynamic simulator), and also compared with laboratory results. Within a single-well tracer test, an assessment of the residual saturation after water filtration and injection of a surfactant-polymer composition was carried out under the following conditions: the target research radius is 3.5 m; porosity 10%, effective reservoir thickness 38 m. Based on the results of SWCTT, an increase in the displacement efficiency of 16.7% was obtained in comparison with water displacement (total surfactant concentration 1%) using an analytical method of interpretation. The adaptation of the SWCTT results on the hydrodynamic model was carried out, the most influencing parameters on the quality of adaptation were determined. The selection and justification of a pilot area for a multi-well pilot project was carried out, a sector hydrodynamic model of the site was built, and calculations were made to assess additional oil production.
{"title":"Planning of Pilot Injection of Surfactant-Polymer Composition to Improve Oil Recovery from Carbonate Reservoir of Kharyaga Oilfield and Evaluation of the Results","authors":"Y. Trushin, A. Aleshchenko, O. Zoshchenko, M. Arsamakov, I. Tkachev, D. S. Kruglov, A. Kornilov, D. Batrshin","doi":"10.2118/206420-ms","DOIUrl":"https://doi.org/10.2118/206420-ms","url":null,"abstract":"\u0000 The paper considers the use of a surfactant-polymer composition for the mobilization of light paraffinic oil from the D3-III carbonate reservoir at a reservoir temperature of 62°C, as well as the results of its tests in field conditions. Earlier, the composition showed its effectiveness on model carbonate cores with salinity from current (50-80 g/l) to reservoir (up to 170 g/l), in the presence of surfactants, type III microemulsions according to Winsor with oil were obtained.\u0000 Based on the results of the filtration experiments performed on our own core from the productive formation D3-III, an increase in the displacement efficiency of surfactant-polymer compositions compared to water was obtained 11–14% (with a total surfactant concentration of 1%), irreversible surfactant losses in water-saturated rock–up to 0, 38 mg/g.\u0000 Displacement efficiency after water and surfactant-polymer composition flooding was also estimated in the field conditions using SWCTT; its results were interpreted by various methods (analytical, in a hydrodynamic simulator), and also compared with laboratory results.\u0000 Within a single-well tracer test, an assessment of the residual saturation after water filtration and injection of a surfactant-polymer composition was carried out under the following conditions: the target research radius is 3.5 m; porosity 10%, effective reservoir thickness 38 m. Based on the results of SWCTT, an increase in the displacement efficiency of 16.7% was obtained in comparison with water displacement (total surfactant concentration 1%) using an analytical method of interpretation. The adaptation of the SWCTT results on the hydrodynamic model was carried out, the most influencing parameters on the quality of adaptation were determined.\u0000 The selection and justification of a pilot area for a multi-well pilot project was carried out, a sector hydrodynamic model of the site was built, and calculations were made to assess additional oil production.","PeriodicalId":11017,"journal":{"name":"Day 2 Wed, October 13, 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74880169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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