Efficient global optimization of reservoir geomechanical parameters based on synthetic aperture radar-derived ground displacements

Abstract

When large volumes of fluids are removed from or injected into underground formations for, e.g., hydrocarbon and water production, CO 2 storage, gas storage, and geothermal energy exploitation, monitoring of surface deformations coupled to numerical modeling improves our understanding of reservoir behavior. The ability to accurately simulate surface displacements, however, is often impaired by limited information on reservoir geometry, waterdrive strength, and fluid-geomechanical parameters characterizing the geologic formations of interest. We have investigated the ability of efficient global optimization (EGO) to reduce the parameter uncertainties usually affecting geomechanical modeling. EGO is used to identify the parameter set that minimizes the difference in land displacements obtained from synthetic aperture radar (SAR)-derived measurements and 3D geomechanical modeling. We have tested the approach on the Tengiz giant oil field, Kazakhstan, where large uncertainties affect our knowledge of geomechanical parameters and pore pressure evolution. SqueeSAR on ENVISAT and RADARSAT-1 images acquired between 2004 and 2007 provided a set of high-precision, high-areal-density subsidence measurements of the test site. Based on the available information, a 3D geomechanical model of the reservoir has been developed using the elastoplastic finite-element code GEPS3D. Our results indicated that EGO efficiently identifies the global optimum in the parameter space, yielding a significant reduction in the difference between modeled and measured land subsidence. The match between simulated and SAR-measured horizontal displacements was developed as validation of the EGO calibration, which thus proved an effective and rather inexpensive method for the simultaneous management of several uncertainties and the reliable quantification of the rock properties.

Delineating ground deformation over the Tengiz oil field, Kazakhstan, using the Intermittent SBAS (ISBAS) DInSAR algorithm

“…Although not recognisable with SBAS, the ISBAS technique enables this deformation to be fully characterised as a subsidence bowl. This is in full agreement with the presence of a subsidence bowl previously computed through geomechanical modelling by Comola et al (2016).…”

“…The SqueeSAR outcome further verifies the ISBAS result by revealing a well-defined subsidence bowl over the reservoir with radar LOS displacement rates of up to -20 mm/year, which is assumed to be almost entirely vertical given the small angle of incidence. Comola et al (2016) also report strong west-east components (8-10 mm/year) in the ground displacement field, however, it is not possible to verify this in the present study owing to the lack of sufficient data from an ascending orbit for 2004-2009. Visually, the SqueeSAR technique provides comparable coverage of the reservoir to that of ISBAS, while the reported average densities for persistent and distributed scatterers are 33 measurements/km 2 and 50 measurements/km 2 , respectively, resulting in ~150,000 measurements (Comola et al, 2016).…”

“…Comola et al (2016) also report strong west-east components (8-10 mm/year) in the ground displacement field, however, it is not possible to verify this in the present study owing to the lack of sufficient data from an ascending orbit for 2004-2009. Visually, the SqueeSAR technique provides comparable coverage of the reservoir to that of ISBAS, while the reported average densities for persistent and distributed scatterers are 33 measurements/km 2 and 50 measurements/km 2 , respectively, resulting in ~150,000 measurements (Comola et al, 2016). Although the density of measurements might appear lower than obtained using ISBAS, a comparison is inappropriate because of inherent differences between the two techniques (i.e., data typepoints vs. pixels)…”

“…Consequently, pixels exhibiting any degree of temporal decorrelation will be immediately discarded in the ALOS SBAS analysis, whereas intermittently coherent pixels are retained in the ISBAS analysis, accounting for the additional ground motion measurements observed here despite utilising C-band data. Comola et al (2016) also processed ENVISAT data for 2004-2007 to ascertain parameters for optimising their geomechnical modelling. The data were processed using the SqueeSAR technique (Ferretti et al, 2011), which utilises both persistent and distributed scatterers in order to enhance the density of ground motion measurements in non-urban areas.…”

“…The Tengiz oil field, with its dynamic semi-arid landscape and lack of built-up areas, represent a type of locality for which comprehensive ground deformation monitoring might be problematic using some DInSAR techniques. Nevertheless, with hydrocarbon production being the single dominant driver of ground deformation and a general paucity of dense vegetation cover, the oil field has been previously investigated using several DInSAR techniques, such as SBAS (Zhantaev et al, 2012) and SqueeSAR (Comola et al, 2016), therefore making it an excellent case study area. Accordingly, this study aims to assess the efficacy of the ISBAS technique for providing a detailed, comprehensive characterisation of deformation over the Tengiz field.…”