Reservoir characterization in an underground gas storage field using joint inversion of flow and geodetic data. (26th August 2015)

• Record Type: Journal Article
• Authors: Jha, B.; Bottazzi, F.; Wojcik, R.; Coccia, M.; Bechor, N.; McLaughlin, D.; Herring, T.; Hager, B. H.; Mantica, S.; Juanes, R.; de Borst, R.; Borja, R. I.; Darve, F.; Pijaudier‐Cabot, G.; Whittle, A. J.
• Is Part Of: International journal for numerical and analytical methods in geomechanics. Volume 39:Number 14(2015)
• Page Start: 1619
• Page End: 1638
• Publication Date: 2015-08-26
• Subjects: Soil mechanics -- Mathematics -- Periodicals; Rock mechanics -- Mathematics -- Periodicals; 624.1510151
• DOI: 10.1002/nag.2427
• Languages: English
• ISSNs: 0363-9061

Abstract

<abstract abstract-type="main" id="nag2427-abs-0001"> <title>Summary</title> <p id="nag2427-para-0001">Characterization of reservoir properties like porosity and permeability in reservoir models typically relies on history matching of production data, well pressure data, and possibly other fluid‐dynamical data. Calibrated (history‐matched) reservoir models are then used for forecasting production and designing effective strategies for improved oil and gas recovery. Here, we perform assimilation of both flow and deformation data for joint inversion of reservoir properties. Given the coupled nature of subsurface flow and deformation processes, joint inversion requires efficient simulation tools of coupled reservoir flow and mechanical deformation. We apply our coupled simulation tool to a real underground gas storage field in Italy. We simulate the initial gas production period and several decades of seasonal natural gas storage and production. We perform a probabilistic estimation of rock properties by joint inversion of ground deformation data from geodetic measurements and fluid flow data from wells. Using an efficient implementation of the ensemble smoother as the estimator and our coupled multiphase flow and geomechanics simulator as the forward model, we show that incorporating deformation data leads to a significant reduction of uncertainty in the prior distributions of rock properties such as porosity, permeability, and pore compressibility. Copyright © 2015 John Wiley & Sons, Ltd.</p> </abstract>