Image-oriented distance parameterization for ensemble-based seismic history matching

Efficient Joint 4D Seismic and Electromagnetic History Matching Using an Ensemble-Based Approach

“…Instead of integrating the inverted saturation field directly, front positions are identified from the inverted saturation field and used as the observed data for history matching. The iterated ensemble smoother combined with a featureoriented distance parameterization method (Zhang and Leeuwenburgh, 2017) is applied to condition the prior permeability ensemble and updated porosity ensemble on the observed fronts.…”

“…A distance parameterization method (Leeuwenburgh and Arts, 2014;Zhang and Leeuwenburgh, 2017) is employed to facilitate the assimilation of the inverted saturation field from seismic and EM data. The distance parameterization utilizes the shape information of the extracted features from the attribute of interest.…”

“…Let and represent the water fronts (i.e., contours) extracted from the inverted and the simulated saturation fields, respectively, with their corresponding binary images (e.g., with 0 indicating the background and with 1 identifying the shape) denoted by the matrices and . Three parameterization schemes were developed in Zhang and Leeuwenburgh (2017). Here, we use the scheme termed as LHDC,…”

Efficient Assimilation of Crosswell Electromagnetic Data Using Ensemble-Based History-Matching Framework

“…In contrast, time-lapse seismic data possess much higher spatial (lateral) resolution and can potentially provide rich information about dynamic changes in the reservoir far from wells locations. Although the quantitative use of timelapse seismic data for history matching still remains a challenging task, significant work has been conducted to overcome this difficulty (Skjervheim et al, 2007;Feng and Mannseth, 2010;Trani et al, 2013;Luo et al, 2017;Zhang and Leeuwenburgh, 2017;. Meanwhile, a growing number of real-field history matching applications using ensemble-based assimilation methods have been presented showing satisfactory results in the literature (Haugen et al, 2008;Zhang and Oliver, 2011;Chen and Oliver, 2014;Abadpour et al, 2018).…”

Quantifying Efficiency Of Field-Wide Geophysical Surveys For Verifying CO2 Plume Conformance During Storage Operations

“…Here we investigate the efficiency associated with the ability to track the position of the CO2-water front (the extent of the plume) as derived from geophysical monitoring survey data. We estimate uncertain storage system properties from differences between observed and model-simulated front positions 7,10 . In this study, the observed time-lapse front positions are set as known contours without doing the actual synthetic or real geophysical survey acquisition.…”