Formation evaluation in low resistivity low contrast (LRLC) shaly sand thin lamination; forward modeling and inversion optimization using genetic algorithm

Abstract

Formation evaluation in thin bed lamination is challenging and classic petrophysical workflow would results in underestimation of true hydrocarbon pore thickness and consequently underestimation of hydrocarbon in place in oil and gas fields. Due to deficiency of conventional well logs to detect thin bed shale sand laminations, they appear as non- hydrocarbon bearing low resistivity interval on well logs. True log response cannot be recorded in thin bed shale sand lamination intervals since thickness of these layers is lower than logging tool resolution. Logging tools can only record the average log response of shale and sand together – rather than true response of sand - anywhere the thickness of each lamination falls below vertical resolution of logging tools. Forward modeling and inversion workflow was applied in a thinly laminated shaly sand reservoir to calculate true hydrocarbon pore thickness. The process of forward modeling and inversion was optimized by using Genetic Algorithm approach by developing a computer code. A new workflow for formation evaluation was proposed for formation evaluation in thin bed shale sand laminations and verified successfully. The result was fully integrated and verified with core, well log and production data. True hydrocarbon pore thickness was increased, and new perforation interval was suggested based on the findings.