Integrating reservoir engineering and satellite remote sensing for (true) continuous time-lapse reservoir monitoring

Abstract

The poem “The Blind Men and the Elephant” is based on an ancient Indian fable in which each man described rather differently what he sensed about an elephant. A similar situation can, and sometimes does, occur in reservoir description. Evidence shows that a reasonably thorough understanding of a reservoir is not very likely without viewing it from many angles and perspectives. This paper will show how two different perspectives of a reservoir—reservoir engineering and satellite remote sensing—can improve reservoir description and even allow (true) continuous time-lapse reservoir monitoring. The idea is simple. If subsidence occurs over an oil field, satellite remote sensing can detect the subsidence, and reservoir engineering can model the subsidence. By integrating reservoir engineering and satellite remote sensing, we can continuously monitor the hydrocarbon production. We use two examples, one from East Mesa Geothermal Field and one from Lost Hills Oil Field, to illustrate the idea. The principle of satellite synthetic aperture radar (SAR) is fairly straightforward. A microwave sensor, which can be on a spacecraft, passes a spot on the ground and takes a “shot” of it. After a certain period, the same sensor passes over the same spot and takes a second “shot” (Figure 1). By comparing the two shots with a reference elevation map, a detailed surface deformation map can be obtained for the period between the passes. Figure 1. Principles of SAR for measuring deformation (from http://www-star.stanford.edu/sar_group/). The image shows two passes of the same microwave sensor over the same location on earth. The difference between the two passes is determined by both earth topography and surface deformation. When data from a reference elevation map or a third pass is used for comparison, the topography effect can be eliminated. What remains is solely surface deformation. SAR can measure surface deformation at very high resolution (a …