GSA Connects 2021 in Portland, Oregon

Paper No. 171-1
Presentation Time: 1:35 PM


XIONG, Fengyang1, JIANG, Zhenxue2, LU, Hailong3, MOORTGAT, Joachim4 and RADONJIC, Mileva1, (1)School of Chemical Engineering, Oklahoma State University, 420 Engineering North, #140, Stillwater, OK 74078, (2)State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum (Beijing), No.18, Road Fuxue, District Changping, Beijing, 102249, China, (3)School of Earth and Space Sciences, Peking University, Beijing, 100871, China, (4)School of Earth Sciences, College of Arts and Sciences, 125 South Oval Mall, COLUMBUS, OH 43210

Gas-in-place (GIP) is a significant parameter in the assessment of gas resources and reserves, design of production strategy, and enhanced gas recovery. To precisely estimate GIP of shales, a direct method often sums experimentally measured desorbed gas by canister desorption testing (CDT), predicted lost gas in the recovery of the fresh core via CDT data in situ on the surface, and measured residual gas in the lab. However, the critical kinetic emission behavior remains poorly understood.

A series of CDTs were collected from our previous work on 33 fresh shale cores. This work, based on experimental observation, proposes a Quasi-Langmuir model, which well fits the experimentally measured data with a coefficient of determination, R2, up to 0.9992. We also compare the model to 5 other potential kinetic gas sorption models, including Pseudo First Order (PFO), Bangham, Elovich, Ritchie, and Pseudo Second Order (PSO) models in terms of the proposed relationship between changes of emitted gas and time. Results show that the Quasi-Langmuir model fits the kinetic data best, followed by Bangham, Ritchie, PSO, PFO, and Elovich models. Ritchie and PSO models give comparable fittings, and the Elovich model deviates from measured data far more than other models.

This work improves understanding of the emission behavior and process of shale gas in CDT, which will provide a robust estimation of lost gas in the borehole, and a more accurate GIP estimate for production in the petroleum industry. Results from this work have significant implications for monitoring the release of natural gas based on adsorption.