2014Unpublished venueRequires access

Facies analysis using multicomponent seismic data in oil-sands reservoir: Case study from Athabasca Oil Sands

Carmen C. Dumitrescu, P. T. M. Vermeulen, Sarah Gammie, Guoping Li

Open publisher page 7 citations

Abstract

Summary Oil-sands and heavy-oil deposits are major players for the future of energy. The world's largest deposits are located in western Canada. The oil sands reservoir in the present study is located in the Upper McMurray Formation, in the Athabasca basin, one of the three major basins in Northern Alberta, Canada. High resolution multicomponent (PP and PS) 3D seismic data was processed using the most advanced workflow in order to image several facies defined based on cores and logs available at wells in the study area. The workflow includes joint PP-PS prestack inversion, neural network analysis and bayesian facies classification. Using the above mentioned workflow in the oil-sand reservoir, we find that the method correctly locates pay and non-pay facies allowing for prediction of oil saturation and reservoir connectivity, including permeability and barrier baffle locations. Probability maps along with maps of the most probable facies are used by the team of geophysicist-geologist-engineer for in-situ operations such as planning of the SAGD horizontal wells.

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Summary Oil-sands and heavy-oil deposits are major players for the future of energy. The world's largest deposits are located in western Canada. The oil sands reservoir in the present study is located in the Upper McMurray Formation, in the Athabasca basin, one of the three major basins in Northern Alberta, Canada. High resolution multicomponent (PP and PS) 3D seismic data was processed using the most advanced workflow in order to image several facies defined based on cores and logs available at wells in the study area. The workflow includes joint PP-PS prestack inversion, neural network analysis and bayesian facies classification. Using the above mentioned workflow in the oil-sand reservoir, we find that the method correctly locates pay and non-pay facies allowing for prediction of oil saturation and reservoir connectivity, including permeability and barrier baffle locations. Probability maps along with maps of the most probable facies are used by the team of geophysicist-geologist-engineer for in-situ operations such as planning of the SAGD horizontal wells.

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Available abstract

Summary Oil-sands and heavy-oil deposits are major players for the future of energy. The world's largest deposits are located in western Canada. The oil sands reservoir in the present study is located in the Upper McMurray Formation, in the Athabasca basin, one of the three major basins in Northern Alberta, Canada. High resolution multicomponent (PP and PS) 3D seismic data was processed using the most advanced workflow in order to image several facies defined based on cores and logs available at wells in the study area. The workflow includes joint PP-PS prestack inversion, neural network analysis and bayesian facies classification. Using the above mentioned workflow in the oil-sand reservoir, we find that the method correctly locates pay and non-pay facies allowing for prediction of oil saturation and reservoir connectivity, including permeability and barrier baffle locations. Probability maps along with maps of the most probable facies are used by the team of geophysicist-geologist-engineer for in-situ operations such as planning of the SAGD horizontal wells.

Key concepts: Oil sands, Geology, Facies, Petroleum engineering, Steam-assisted gravity drainage, Unconventional oil, Petrology, Asphalt

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