A New Inflow Performance Relationship for Shale Gas Reservoirs Using Well Logs and Geochemistry Data

Abstract

Abstract Exploiting the unconventional oil and gas resources has been sparked recently. Evaluating the well productivity in shale formations based on bare test rates is challenging and requires extensive work of simulation and extended periods of well testing. This work introduces a new, simple, and efficient IPR model for estimating the production performance from unconventional shale reservoirs at early stages of drilling and production. The implementation of this IPR model depends mainly on the integration between well logs and geochemical pyrolysis data to estimate the hydrocarbon potential in the reservoir. The proposed IPR model was applied using real data from shale gas reservoirs. In this work, the well logs were initially analyzed to stratify the pay zone and to obtain the gas saturation. Then, an analytical correlation was derived to convert the organic richness indicator of the free and adsorbed gas (S1) to an incremental porosity and gas saturation values. After that, the final porosity and saturation profiles, along with the other petrophysical data were incorporated into a fractured reservoir simulation model using a commercial reservoir simulator (CMG). Then, the production outcomes of the simulation model were collected to be used in generating the IPR model as a function of the petrophysical and the pyrolysis data. The results showed an excellent correlation between well performance, logging, and the pyrolysis data. The developed IPR formula was found in the form of famous Fitkovich’s back pressure model which fitted the simulator generated production data at different reservoir pressures with R2 value of 0.99 for different reservoir pressures. Moreover, the exponent (n) in Fetkovich’s IPR model which ranges from 0.5 to 1 in conventional reservoirs, was found to be greater than 1 in unconventional shale gas reservoirs. This finding was examined in a case study using real production data. On the other hand, the log C value, which is involved in the y-intercept of the logarithmic transformation of Fetkovich IPR, was seen to be dependent on reservoir’s characteristics and geochemical properties such as bed thickness, gas saturation, porosity, and organic production index (PI). Overall, the study aims to develop a simple IPR model to estimate well productivity in shale gas reservoirs based on the available logging and pyrolysis data during the early stages of drilling and completion. Moreover, the proposed model can be integrated with Logging While Drilling (LWD) operation for real-time estimation of well productivity. For the first time, the geochemical properties are integrated with the logging data to provide an IPR model that considers the free and adsorbed gas in the shale formations.