Affiliation:
1. The University of Texas at Austin, Jackson School of Geological Sciences, Austin, Texas, USA..
Abstract
Large-scale subsurface injection of [Formula: see text] has the potential to reduce emissions of atmospheric [Formula: see text] and improve oil recovery. Studying the effects of injected [Formula: see text] on the elastic properties of the saturated reservoir rock can help to improve long-term monitoring effectiveness and accuracy at locations undergoing [Formula: see text] injection. We used two vintages of existing 3D surface seismic data and well logs to probabilistically invert for the [Formula: see text] saturation and porosity at the Cranfield reservoir using a double-difference approach. The first step of this work was to calibrate the rock-physics model to the well-log data. Next, the baseline and time-lapse seismic data sets were inverted for acoustic impedance [Formula: see text] using a high-resolution basis pursuit inversion technique. The reservoir porosity was derived statistically from the rock-physics model based on the [Formula: see text] estimates inverted from the baseline survey. The porosity estimates were used in the double-difference routine as the fixed initial model from which [Formula: see text] saturation was then estimated from the time-lapse [Formula: see text] data. Porosity was assumed to remain constant between survey vintages; therefore, the changes between the baseline and time-lapse [Formula: see text] data may be inverted for [Formula: see text] saturation from the injection activities using the calibrated rock-physics model. Comparisons of inverted and measured porosity from well logs indicated quite accurate results. Estimates of [Formula: see text] saturation found less accuracy than the porosity estimates.
Publisher
Society of Exploration Geophysicists
Cited by
1 articles.
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