A new technique for solving pressure–rate deconvolution problem in pressure transient testing

Skorik, Georgy; Васин, В. В.; Kuchuk, Fikri J.

doi:10.1007/s10665-016-9854-x

Cited by 8 publications

(2 citation statements)

References 6 publications

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“…Water 2018, 10, x FOR PEER REVIEW 3 of 14 [19][20][21]. Using pressure derivative data in deconvolution leads to a nonlinear least-squares objective function that is different from those used in the earlier deconvolution methods and eliminates the dependency of the deconvolved responses on the initial reservoir pressure.…”

Section: The Division Of Production Stagesmentioning

confidence: 99%

“…A small error in the initial reservoir pressure could make a significant difference in the late time periods of the deconvolved responses that can lead to an incorrect interpretation model, particularly misinterpretation of the boundaries. The method presented above is based on pressure derivative data rather than pressure data that are used in all published deconvolution algorithms [19][20][21]. Using pressure derivative data in deconvolution leads to a nonlinear least-squares objective function that is different from those used in the earlier deconvolution methods and eliminates the dependency of the deconvolved responses on the initial reservoir pressure.…”

Section: Introductionmentioning

confidence: 99%

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A Study on Optimization of CBM Water Drainage by Well-Test Deconvolution in the Early Development Stage

Gao

Liu

Guo³

et al. 2018

Water

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Different from the conventional gas reservoir, coalbed methane is developed mainly by water drainage, which leads methane desorption after reservoir pressure drop. Water drainage at a reasonable speed in the early development stage is the key for enhancing later gas performance. Therefore, the investigation radius, which reflects the pressure drop region scale, is studied by deconvolution well-test to find the reasonable water drainage speed in the early period. First, the early production data (well-bottom pressure and water rate) are processed by deconvolution algorithm, and then the pressure data under unit rate is obtained to invert the comprehensive reservoir permeability and investigation radius. This deconvolution method can save the cost of the conventional well-test, and avoid reservoir damage caused by frequent well shut-off. The feasibility of the deconvolution test method is verified by comparing its interpretation results with those of the conventional pressure drop/build-up test. For a field application, the 29 wells’ comprehensive permeability are inverted by the deconvolution well-test using early water production data of Hancheng block. Furthermore, their investigation radius and pressure drawdown gradient are calculated, and the performance optimization is determined by relationship analysis between working fluid level and steady gas production rate. We find that well-bottom pressure and reservoir pressure should decrease steadily in the early development stage, with the working fluid level declining less than 1 m/d (1 m per day) in wellbore, and the pressure drawdown gradient declining less than 2.8 MPa/100 m.

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Section: The Division Of Production Stagesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%