Applying CRM Model to Study Well Interference

Tyumen State University Herald. Physical and Mathematical Modeling. Oil, Gas, Energy


Release:

2018, Vol. 4. №4

Title: 
Applying CRM Model to Study Well Interference


For citation: Ruchkin A. A., Stepanov S. V., Knyazev A. V., Stepanov A. V., Korytov A. V., Avsyanko I. N. 2018. “Applying CRM Model to Study Well Interference”. Tyumen State University Herald. Physical and Mathematical Modeling. Oil, Gas, Energy, vol. 4, no 4, pp. 148-168. DOI: 10.21684/2411-7978-2018-4-4-148-168

About the authors:

Alexander A. Ruchkin, Cand. Sci. (Tech.), Expert, Tyumen Petroleum Research Center; eLibrary AuthorID, aaruchkin@tnnc.rosneft.ru

Sergey V. Stepanov, Dr. Sci. (Tech.), Professor, Department of Applied and Technical Physics, University of Tyumen; Senior Expert, Tyumen Petroleum Research Center; eLibrary AuthorID, svstepanov@tnnc.rosneft.ru

Aleksandr V. Knyazev, Senior Manager, Tyumen Petroleum Research Center; avknyazev@tnnc.rosneft.ru

Anatoliy V. Stepanov, Cand. Sci. (Phys.-Math.), Associate Professor, Department of Applied and Technical Physics, University of Tyumen; Expert, Tyumen Petroleum Research Center; avstepanov5@tnnc.rosneft.ru

Aleksandr V. Korytov, Section Head, Tyumen Petroleum Research Center; avkorytov2@tnnc.rosneft.ru

Igor N. Avsyanko, Head of Field Development Divison, RN-Nyaganneftegaz; inavsyanko@nng.rosneft.ru

Abstract:

The quantitative evaluation of producer and injector well interference based on well operation data (profiles of flow rates/injectivities and bottomhole/reservoir pressures) is an inverse problem. The solution to that issue demonstrates significant ambiguity. Solving practical field development problems, such as injection control, requires more than a single ambiguous (unreliable) solution. Therefore, the evaluation of well interference demands studying the solutions to an inverse problem.

This article aims to study the solution using the CRM model, namely, the variability of the quantitative estimation of well interference coefficients for different options of objective function formulation using five optimization methods and applying different sets of constraints on control parameters.

The studies were conducted on a synthetic oil accumulation model. The results of studies for one of the synthetic accumulations in a heterogeneous reservoir are shown. The flow simulation data was used as a standard, while the interference coefficients were calculated from the stream lines as a postprocessing procedure.

The authors provide an example of testing the developed injection control method for a real reservoir. The results confirmed the possibility to redistribute injection between injection wells.

The authors note that the process of solving the inverse problem on the CRM model on a standard workstation takes approximately a few minutes. This is incommensurably less than the time required to solve an inverse problem of matching a three-dimensional flow simulation model. Therefore, an advantage of simplified models, including analytical CRM models, is the possibility to obtain a prompt solution.

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