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A systematic machine learning method for reservoir identification and production prediction

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Petroleum Science 2023年第1期20卷 295-308页

作者： Wei Liu zhangxin chen Yuan Hu Liuyang Xu Department of Chemical and Petroleum Engineering University of CalgaryABCanada Rockeast Energy Ltd. CalgaryABCanada Jilin Oilfield CNPCChangchunJilin130000China

Reservoir identification and production prediction are two of the most important tasks in petroleum exploration and *** learning(ML)methods are used for petroleum-related studies,but have not been applied to reservoir identification and production prediction based on reservoir *** forecasting studies are typically based on overall reservoir thickness and lack accuracy when reservoirs contain a water or dry layer without oil *** this paper,a systematic ML method was developed using classification models for reservoir identification,and regression models for production *** production models are based on the reservoir identification *** realize the reservoir identification,seven optimized ML methods were used:four typical single ML methods and three ensemble ML *** methods classify the reservoir into five types of layers:water,dry and three levels of oil(I oil layer,II oil layer,III oil layer).The validation and test results of these seven optimized ML methods suggest the three ensemble methods perform better than the four single ML methods in reservoir *** XGBoost produced the model with the highest accuracy;up to 99%.The effective thickness of I and II oil layers determined during the reservoir identification was fed into the models for predicting *** thickness considers the distribution of the water and the oil resulting in a more reasonable production prediction compared to predictions based on the overall reservoir *** validate the superiority of the ML methods,reference models using overall reservoir thickness were built for *** models based on effective thickness outperformed the reference models in every evaluation *** prediction accuracy of the ML models using effective thickness were 10%higher than that of reference *** the personal error or data distortion existing in traditional methods,this novel system realizes r

关键词： Reservoir identification Production prediction Machine learning Ensemble method

Shale gas transport in nanopores with mobile water films and water bridge

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Petroleum Science 2023年第2期20卷 1068-1076页

作者： Ran Li zhangxin chen Keliu Wu Jinze Xu Department of Chemical and Petroleum Engineering University of CalgaryCalgaryAlbertaT2N 1N4Canada State Key Laboratory of Petroleum Resources and Prospecting China University of Petroleum(Beijing)Beijing102249China

Gas flow properties in nanopores are significantly determined by the flow patterns. Slug flow pattern is a potential water–gas two phase flow pattern, in which gas molecules flow in form of gas slugs and water molecules separate gas slugs. Considering water slippage, a portion of water molecules accumulates at the wall with lower mobility, while the remaining water molecules take the shape of a water bridge. Adopting foam apparent viscosity model to represent slug rheological behavior, how water bridge disturbs on gas flow capacity is estimated. The results are compared with the water–gas two phase flow model that assumes annular flow pattern as well as the single gas flow model without the consideration of water. The comparison illustrates that gas molecular movement is significantly hindered by flow space reduction and loss of gas slippage. The impact from water phase of slug flow pattern is more significant than that of annular flow pattern on gas flow capacity. It is discovered that larger nanopores improve gas flow capacity while maintaining bulk water layer thickness and increasing water bridge thickness tend to reduce gas transport ability. A better understanding of the structure and transport of water and gas molecules is conducive to figure out the specific gas–water flow behavior and predict shale gas production.

关键词： Shale gas Water bridge Water film Nanopore

Intelligent Petroleum Engineering

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Engineering 2022年第11期18卷 27-32页

作者： Mohammad Ali Mirza Mahtab Ghoroori zhangxin chen Department of Chemical and Petroleum Engineering University of CalgaryCalgaryAB T2N 1N4Canada

Data-driven approaches and artificial intelligence(AI)algorithms are promising enough to be relied on even more than physics-based methods;their main feed is data which is the fundamental element of each *** algorithms learn from data and unveil unseen patterns out of it The petroleum industry as a realm where huge volumes of data are generated every second is of great interest to this new *** the oil and gas industry is in the transition phase to oilfield digitization,there has been an increased drive to integrate data-driven modeling and machine learning(ML)algorithms in different petroleum engineering *** has been widely used in different areas of the *** extensive studies have been devoted to exploring AI applicability in various disciplines of this industry;however,lack of two main features is *** of the research is either not practical enough to be applicable in real-field challenges or limited to a specific problem and not *** must be given to data itself and the way it is classified and *** there are sheer volumes of data coming from different disciplines,they reside in departmental silos and are not accessible by *** order to derive as much insight as possible out of data,the data needs to be stored in a centralized repository from where the data can be readily consumed by different applications.

关键词： Artificial intelligence Machine learning Intelligent reservoir engineering Text mining Intelligent geoscience Intelligent drilling engineering

Data-driven model for predicting production periods in the SAGD process

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Petroleum 2022年第3期8卷 363-374页

作者： Ziteng Huang Min Yang Bo Yang Wei Liu zhangxin chen Department of Chemical and Petroleum Engineering University of Calgary2500 University Drive NWCalgaryT2N 1N4Canada

Many studies have analyzed the cumulative production performance in the SAGD(steam assisted gravity drainage)process by data-driven models but a study based on these models for a dynamic analysis of a SAGD production period is still *** is important for engineers to define the production period in a SAGD process as it has a stable and high oil production rate and engineers need to reset operational conditions after the production period *** this paper,a series of SAGD models were constructed with selected ranges of reservoir properties and operational *** SAGD production period parameters,including the start date,end date,and duration,are collected based on the simulated production *** neural network,extreme gradient boosting,light gradient boosting machine,and catboost were constructed to reveal the hidden relationships between twelve input parameters and three output *** data-driven models were trained,tested,and *** results showed that compared with the other output parameters,the R^(2) of the end date is the highest and it becomes higher with a larger training data *** extreme gradient boosting algorithm is a better choice to predict the Start date while the artificial neural network generates better prediction for the other two output *** study shows a significant potential in the use of data-driven models for the SAGD production dynamic *** results also serve to support the utilization of the datadriven models as efficient tools for predicting a SAGD production period.

关键词： Steam assisted gravity drainage Data-driven model Artificial neural network Extreme gradient boosting Light gradient boosting machine CatBoost

Editorial for the Special Issue on Unconventional and Intelligent Oil and Gas Engineering

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Engineering 2022年第11期18卷 1-2页

作者： Gensheng Li Jinsheng Sun zhangxin chen Zhenhua Rui State Key Laboratory of Petroleum Resources and Prospecting China University of Petroleum(Beijing)Beijing 102249China School of Petroleum Engineering China University of Petroleum(East China)Qingdao 266580China China National Petroleum Corporation Beijing 100007China Department of Chemical and Petroleum Engineering University of CalgaryCalgaryAB T2N 1N4Canada

A key global challenge in the 21st century is how to secure sustainable access to energy for a growing global population—set to reach 10 billion by 2035—while coping with the threat of dangerous climate *** oil and gas industry will still play an essential role in the energy transition by providing affordable and reliable energy to improve living ***,producing this energy with decreasing emissions supports a net-zero world.

关键词： global dangerous providing

Effect of quadratic pressure gradient term on a one-dimensional moving boundary problem based on modified Darcy's law

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Acta Mechanica Sinica 2016年第1期32卷 38-53页

作者： Wenchao Liu Jun Yao zhangxin chen Yuewu Liu Institute of Mechanics Chinese Academy of Sciences School of Petroleum Engineering China University of Petroleum (Huadong) Department of Chemical and Petroleum Engineering Schulich School of Engineering University of Calgary

A relatively high formation pressure gradient can exist in seepage flow in low-permeable porous media with a threshold pressure gradient, and a significant error may then be caused in the model computation by neglecting the quadratic pressure gradient term in the governing equations. Based on these concerns, in consideration of the quadratic pressure gradient term, a basic moving boundary model is constructed for a one-dimensional seepage flow problem with a threshold pressure gradient. Owing to a strong nonlinearity and the existing moving boundary in the mathematical model, a corresponding numerical solution method is presented. First, a spatial coordinate transformation method is adopted in order to transform the system of partial differential equa- tions with moving boundary conditions into a closed system with fixed boundary conditions; then the solution can be sta- bly numerically obtained by a fully implicit finite-difference method. The validity of the numerical method is verified by a published exact analytical solution. Furthermore, to compare with Darcy＇s flow problem, the exact analytical solution for the case of Darcy＇s flow considering the quadratic pressure gradient term is also derived by an inverse Laplace transform. A comparison of these model solutions leads to the conclu- sion that such moving boundary problems must incorporate the quadratic pressure gradient term in their governing equa- tions; the sensitive effects of the quadratic pressure gradient term tend to diminish, with the dimensionless threshold pres- sure gradient increasing for the one-dimensional problem.

关键词： Quadratic pressure gradient term Thresholdpressure gradient Porous media Numerical solution Moving boundary

EFFICIENT LINEAR SCHEMES WITH UNCONDITIONAL ENERGY STABILITY FOR THE PHASE FIELD MODEL OF SOLID-STATE DEWETTING PROBLEMS

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Journal of Computational Mathematics 2020年第3期38卷 452-468页

作者： Jie chen Zhengkang He Shuyu Sun Shimin Guo zhangxin chen School of Mathematics and Statistics Xi'an Jiaotong UniversityXi'an 710049China Computational Transport Phenomena Laboratory Division of Physical Science and EngineeringKing Abdullah University of Science and TechnologyThuwal 23955-6900Kingdom of Saudi Arabia School of Mathematics and Statistics Xi'an Jiaotong Universityy Xi'an 710049China Department of Chemical&Petroleum Engineering Schulich School of EngineeringUniversity of Calgary2500 University Drive N.W.CalgaryAlberta T2N 1N4Canada

In this paper,we study linearly first and second order in time,uniquely solvable and unconditionally energy stable numerical schemes to approximate the phase field model of solid-state dewetting problems based on the novel"scalar auxiliary variable"(SAV)approach,a new developed efficient and accurate method for a large class of gradient *** schemes are based on the first order Euler method and the second order backward differential formulas(BDF2)for time discretization,and finite element methods for space *** proposed schemes are proved to be unconditionally stable and the discrete equations are uniquely solvable for all time *** numerical experiments are presented to validate the stability and accuracy of the proposed schemes.

关键词： Phase field models Solid-state dewetting SAV Energy stability Surface diffusion Finite element method

Will the future of shale reservoirs lie in CO2 geological sequestration?

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中国科学：技术科学英文版 2020年第7期63卷 1154-1163页

作者： ZHAN Jie chen zhangxin ZHANG Ying ZHENG ZiGang DENG Qi School of Petroleum Engineering Xi'an Shiyou UniversityXi'an 710065China Engineering Research Center of Development and Management for Low to Ultra-Low Permeability Oil&Gas Reservoirs in West China Ministry of EducationXi'an Shiyou UniversityXi'an 710065China Department of Chemical&Petroleum Engineering University of CalgaryCalgary T2N1N4Canada Natural Gas Engineering Design Department Xi'an Changqing Technology Engineering Co.Ltd.Xi'an 710018China Petroleum Exploration and Development Research Institute PetroChina Changqing Oilfield CompanyXi'an 710018China State Key Laboratory of Oil&Gas Reservoir Geology and Exploitation Southwest Petroleum UniversityChengdu 610500China

CO2 geological sequestration in a depleted shale gas reservoir is a promising method to address the global energy crisis as well as to reduce greenhouse gas emissions. Though improvements have been achieved by many researchers, the carbon sequestration and enhanced gas recovery(CS-EGR) in shale formations is still in a preliminary stage. The current research status of CO2 sequestration in shale gas reservoirs with potential EGR is systematically and critically addressed in the paper. In addition, some original findings are also presented in this paper. This paper will shed light on the technology development that addresses the dual problem of energy crisis and environmental degradation.

关键词： shale gas reservoir CO2 sequestration EGR indexes criteria for prescreening sorption

An analytical model for water-oil two-phase flow in inorganic nanopores in shale oil reservoirs

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Petroleum Science 2021年第6期18卷 1776-1787页

作者： Ran Li zhangxin chen Keliu Wu Xing Hao Jinze Xu Department of Chemical and Petroleum Engineering University of CalgaryCalgaryAlbertaT2N 1N4Canada State Key Laboratory of Petroleum Resources and Prospecting China University of PetroleumBeijing102249China Illinois Institute of Technology ChicagoIL60616United States

The existence of water phase occupies oil flow area and impacts the confined oil flow behavior at the solid substrate in inorganic nanopores of shale oil reservoirs,resulting in a completely different flow pattern when compared with the single oil phase *** study proposes an analytical model to describe the water-oil two-phase *** this model,water slippage at the solid substrate is considered while oil slip is introduced to calculate the oil movement at the solid-oil boundary in dry *** is proven that the oil flow profiles of both the two-phase model and single-phase model show parabolic shapes,but the oil flow capacity drops when water takes up the flow space and the impact of water is more significant when the pore dimension is smaller than 30 ***,the oil flow velocity at a pore center is found to drop linearly given a larger water saturation in wet *** effects of surface wettability and oil properties on water-oil flow are also *** with the existing singlephase models,this model describes oil flow pattern in the wet condition with the incorporation of the influence of nanopore properties,which better predicts the oil transport in actual reservoir ***-oil relative permeability curves are also obtained to improve oil yield.

关键词： Shale oil Water films Two-phase flow Nanopore