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MODEL AND METHOD OF well test ANALYSIS FORwellS WITH VERTICAL FRACTURE

Applied Mathematics and Mechanics(English Edition) 2005年第5期26卷 571-578页

作者：郭大立曾晓慧赵金洲刘慈群 Department of Computer Science Southwest Petroleum InstituteChengdu 610500 P.R.China Department of Petroleum Engineering Southwest Petroleum InstituteChengdu 610500 P.R.China Department of Postgraduate Southwest Petroleum InstituteChengdu 610500 P.R.China Institute of Porous Flow and Fluid Mechanics Chinese Academy of ScienceLangfang Hebei 065007 P.R.China

Based on the flow mechanism of hydraulic fractured wells, through integrating linear-flow model and effective well-radius model, a new model of well test analysis for wells with vertical fracture was established. In the model, wellbore storage, the damage in the wall of fracture and all kinds of boundary conditions are considered. The model is concise in form, has intact curves and computes fast, which may meet the demand of real-time computation and fast responded well test interpretation. A new method to determine effective well radius was presented, and the correlation between effective well radius and the fracture length, fracture conductivity, skin factor of fracture was given. Matching flow rate or pressure tested, the optimization model that identified formation and fracture parameters was set up. The automatic matching method was presented by synthetically using step by step linear least square method and sequential quadratic programming. At last, the application was also discussed. Application shows that all of these results can analyze and evaluate the fracturing treatment quality scientifically and rationally, instruct and modify the design of fracturing and improve fracturing design level.

关键词： vertical fracture well test fluid flow through porous medium model automatic matching method

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A robust deep structured prediction model for petroleum reservoir characterization using pressure transient test data

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Petroleum Research 2022年第2期7卷 204-219页

作者： Rakesh Kumar Pandey Anil Kumar Ajay Mandal Department of Petroleum and Energy Studies School of Engineering and TechnologyDIT UniversityDehradun248009India Data Science Research Group School of ComputingDIT UniversityDehradun248009India Department of Petroleum Engineering Indian Institute of Technology(Indian School of Mines)Dhanbad826004India

A robust deep learning model consisting of long short-term memory and fully connected neural net-works has been proposed to automatically interpret homogeneous petroleum reservoirs having infinite,no flow,and constant pressure outer boundary conditions.The pressure change data recorded during the well test operation along with its derivative is input into the model to perform the classification for identifying the reservoir model and,further,regression to estimate output parameter.Gaussian noise was added to analytical models while generating the synthetic training data.The hyperparameters were regulated to perform model optimization,resulting in a batch size of 64,Adam optimization algorithm,learning rate of 0.01,and 80:10:10 data split ratio as the best choices of hyperparameters.The perfor-mance accuracy also increased with an increase in the number of samples during training.Suitable classification and regression metrics have been used to evaluate the performance of the models.The paper also demonstrates the prediction performance of the optimized model using simulated and actual oil well pressure drawdown test cases.The proposed model achieved minimum and maximum relative errors of 0.0019 and 0.0308,respectively,in estimating output for the simulated test cases and relative error of 0.0319 for the real test case.

关键词： well test Reservoir characterization Automatic interpretation Prediction model Hyperparameter tuning Performance indicator

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INVESTIGATION OF THE FLOW IN FRACTAL RESERVOIR INCLUDING THE EFFECTS OF QUADRATIC GRADIENT TERM

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Journal of Hydrodynamics 2004年第4期16卷 474-480页

作者： YAOYue-dong LIXiang-fang TONGDeng-ke InstituteofPetroleumandGasEngineering UniversityofPetroleumBeijing102249China DepartmentofAppliedMathematics UniversityofPetroleumDongying257062China

According to the assumption of slightly compressible fluid, the quadraticgradient term in the nonlinear partial differential equations for the traditional well-test model isusually neglected. The linear partial differential equation is thus established. It is known thatneglecting the quadratic gradient term results in errors for long-time well tests. A nonlinear flowmodel for fractal medium is constructed and the quadratic gradient term is considered. The exactsolutions of the fractal reservoir models are obtained by Laplace transform and Weber transform in aconstant-rate and constant-pressure production for an infinitely large system. This paper addressesthe variation of pressure with fluid compressibility coefficient and fractal reservoir parameters.The plots of the typical pressure curves are constructed, and the results can be applied towell-test analysis.

关键词： fractal model nonlinear exact solution typical curve plots well test

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