1887
Volume 70, Issue 6
  • E-ISSN: 1365-2478

Abstract

ABSTRACT

Steam‐assisted gravity drainage reservoirs require an immense amount of energy and water resources, and proper monitoring of steam evolution and depletion patterns is integral to the economic and environmental efficiency of the operation. Muon tomography is a passive sensing technique, which has proven to successfully model density anomalies in a variety of applications but has not yet been applied to the oil and gas field. A previous study simulated muon intensity data to model density changes in a realistic steam‐assisted gravity drainage reservoir at 1.25 and 5 years after initial production. The results showed that muon tomography is a promising technique for monitoring steam‐assisted gravity drainage reservoirs with high spatial resolution and over short time intervals of weeks to months. Here we demonstrate the advantage of using vertical gravity gradient data and muon tomography data in a joint inversion to improve the muon‐only inverse models. Forward models for simulated muon and gravity gradient data are jointly inverted for a realistic steam‐assisted gravity drainage reservoir at 230 and 130 m total vertical depth at 1.25 years after initial production. Results show that the addition of gravity gradient data helps to constrain the density change models mainly in depth and to a smaller extent laterally. For a sparse muon sensor array of 48 sensors over a reservoir at depth, the joint inversion using gravity gradient data reduces the difference between the inverse and true model by 12% compared to a muon‐only inversion. The improvement is smaller at depth with 6%. The improvement in resolvability metrics is summarized, and limitations are discussed. The addition of multiple data types in a joint inversion improves the resulting models leading to an overall decrease in model uncertainty which can be used for improved operational efficiency in steam‐assisted gravity drainage operations.

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2022-06-16
2022-06-27
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