An Original Theoretical Contribution to Production Data Analysis for Unconventional Tight Gas Reservoirs: Extending Rate Transient Analysis to Dual-Porosity Desorbing Systems in Northern Nigerian Basin Sequences

📖 ABSTRACT/OVERVIEW

Rate transient analysis theory for tight gas reservoirs has been extensively developed for matrix-dominated flow systems but lacks a complete theoretical treatment for dual-porosity systems where significant gas desorption from organic matter contributes to production in addition to conventional matrix and fracture free gas flow. This study develops an original theoretical extension of rate transient analysis to dual-porosity desorbing gas systems applicable to northern Nigerian tight gas basin sequences including the Songhai Formation and Gongola Basin Cretaceous sequences. The theoretical development derives new dimensionless rate decline solutions for a dual-porosity linear composite system with Langmuir-type desorption boundary conditions by applying Laplace transform methods to the coupled fracture-matrix-desorption flow equations. Original dimensionless type curves are derived that explicitly show the distinctive production signatures attributable to desorption: a characteristic late-time rate decline flattening not present in non-desorbing systems and an apparent matrix permeability that progressively increases as desorption-driven matrix pressure gradient develops. Inversion algorithms based on Stehfest numerical Laplace inversion are implemented to enable automatic type curve matching and parameter estimation. The new type curves are validated against finite difference numerical simulation results for representative northern Nigerian tight gas reservoir properties. Application to synthetic production data from two hypothetical Gongola Basin wells demonstrates that omitting desorption from conventional rate transient analysis causes up to 34 percent underestimation of gas in place. Keywords: rate transient analysis, dual-porosity, desorption, tight gas, northern Nigerian basins.

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