Inferences Derived from Reservoir Permeability Estimation Using Static and Dynamic Data: Core Data Analysis Versus Drawdown Tests

Francis Nwabia, Jude Osamor, Robinson Madu, Nkemakolam Izuwa and Anthony Chikwe 2021. Inferences Derived from Reservoir Permeability Estimation Using Static and Dynamic Data: Core Data Analysis Versus Drawdown Tests. in: Jia'en Lin (ed.) IPPTC 2021: Proceedings of the 2021 International Petroleum and Petrochemical Technology Conference Springer Nature. pp. 184-196

Chapter titleInferences Derived from Reservoir Permeability Estimation Using Static and Dynamic Data: Core Data Analysis Versus Drawdown Tests
AuthorsFrancis Nwabia, Jude Osamor, Robinson Madu, Nkemakolam Izuwa and Anthony Chikwe
EditorsJia'en Lin
Abstract

Reservoir characterization using well test analysis is often plagued with assumptions such as reservoir homogeneity and average permeability interpretation, making it difficult to use its interpretations for future reservoir predictions. Static information of the reservoir is used where possible in conjunction with the well test information to design a reservoir model for prediction of the field behavior, but this relationship is not easy to establish. It is therefore necessary to establish a consistent relationship between these two methods or justify inconsistencies in the methods for reservoir properties in order to improve the confidence in the prediction of future reservoir fluid behavior.

In this study, a semi-log plot was employed for the analysis of a drawdown test performed on an oil reservoir penetrated by two wells (Wel1 – M in the East and Well – N in the North West) to estimate reservoir permeability. This is followed by type curve matching as a validation tool for the permeability results obtained from semi-log plot analysis. The type curve matching is believed to be a better approximation since they are pre-calculated graphic solutions to diffusivity equations and take multiple parameters into consideration. Next is the determination of reservoir permeability using analysis of core data through derivable correlation existing between the porosity and permeability. Correlation functions between porosity and permeability is established using the classical method which considers the whole cored interval of the reservoir region as one unit and the FZI technique which considers different cored intervals as hydraulic units or facies. The consistency of the results obtained from well test with the geologist’s porosity map and core data is assessed and the factors contributing to possible discrepancies are discussed and justified.

Based on the assumptions considered for the study, the results show that the permeability values obtained for Well – N using the different approaches are consistent with a minor percentage difference (Well – N - semi-log 145.83 mD; type curve 181 mD; core data 138.40 mD). However, although there is consistency in permeability between the result from semi-log analysis and type curve matching for Well – M, there is an observable wide discrepancy in these permeabilities with that obtained from core data analysis. Permeability map obtained from simulation for Well – M shows similar value of permeability with that of core data and it is therefore believed that this discrepancy could be caused by the average value of permeability usually estimated from drawdown tests and in this case, Well – M is surrounded by region of lower permeabilities.

Book titleIPPTC 2021: Proceedings of the 2021 International Petroleum and Petrochemical Technology Conference
Page range184-196
Year2021
PublisherSpringer Nature
Publication dates
Published12 Mar 2022
ISBN9789811694264
9789811694271
Digital Object Identifier (DOI)https://doi.org/10.1007/978-981-16-9427-1_18
Web address (URL)http://dx.doi.org/10.1007/978-981-16-9427-1_18
JournalProceedings of the 2021 International Petroleum and Petrochemical Technology Conference

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