Integrated nonlinear regression analysis of tracer and well test data

Date

2003-08-01

Author

Akın, Serhat

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One frequent observation from conventional pressure transient test analysis is that field data match mathematical models derived for homogeneous systems. This observation suggests that pressure data as presently interpreted may not contain details concerning certain reservoir heterogeneities. On the other hand, tracer tests may be more sensitive to heterogeneous elements present in the reservoir because of the convective nature of the flow test. In this study, a possible improvement of conventional pressure transient and tracer test analysis by integrating them using the nonlinear least square (LS) regression method is investigated. To achieve this goal, a correlation between permeability and dispersivity is used to couple the response of both tests. A multi-fracture tracer test model was coupled with double porosity pressure models using a commercial spreadsheet. The proposed method is tested using experimental well test and tracer test data obtained from a fractured geothermal reservoir model where fracture apertures and distributions were known. It has been observed that changing injection-production well depths resulted in different analyses primarily due to changing flow paths. The combination of multi-fracture tracer test model with dual-porosity pressure transient model described the physics of the experiments better than the others did. It has been also observed that the obtained solutions are highly constrained.

Subject Keywords

Fuel Technology, Geotechnical Engineering and Engineering Geology

URI

https://hdl.handle.net/11511/42519

Journal

JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING

DOI

https://doi.org/10.1016/s0920-4105(03)00038-x

Collections

Department of Petroleum and Natural Gas Engineering, Article

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Citation Formats

S. Akın, “Integrated nonlinear regression analysis of tracer and well test data,” JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING, pp. 29–44, 2003, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/42519.