Practical Engineering Issues of 4D Seismic Reservoir Monitoring

Abstract

Abstract "4D seismic reservoir monitoring" is the process of repeating 3D seismic surveys over a producing reservoir in time-lapse mode. It has a potentially huge impact in reservoir management because it is the first technique that may allow us to directly image dynamic reservoir processes such as fluid movement, pressure build-up, and heat flow in a reservoir in a true volumetric sense. However, its simple underlying concept is complicated by practical operational issues. These include having the right mix of business to justify a 4D seismic project, a favorable technical risk assessment and feasibility study, highly repeatable seismic acquisition survey design, careful high-resolution seismic data processing, and an ultimate reconciliation of 4D seismic images with independent reservoir borehole data and history-matched flow simulations. The practical difficulties associated with 4D seismic suggest that this new technology is not a panacea, but rather that it is an exciting emerging technology that requires very careful analysis to be useful. Introduction "4D seismic reservoir monitoring" is the process of repeating 3D seismic surveys over a reservoir in time-lapse mode to look for differences caused by production. The potential exists for dramatic benefits to reservoir management because it is the first technique that may allow us to directly image dynamic reservoir processes such as fluid movement, pressure build-up, and heat flow in a reservoir in a true volumetric sense. To understand this, let us review the seismic method, and then consider what advantages the time-lapse aspect of 4D seismic brings. In a single 3D seismic survey, seismic waves are generated by sources (dynamite, airguns, etc.) at or near the earth's surface. These source waves reflect off of subsurface seismic impedance contrasts, which are a function of rock and fluid compressibility, shear modulus and bulk density, and are recorded as they arrive back at the earth's surface. The recorded waves form the classic wiggle traces where high positive amplitude portions are often filled in on a black and white image to enhance visual contrast and show lateral continuity. A wave-equation imaging algorithm is applied to the recorded reflection data to create 3D seismic images of the reservoir rock and fluid property (seismic impedance) contrasts. 4D seismic analysis simply involves repeating the 3D seismic surveys and analyzing images in time-lapse mode, to monitor time-varying fluid-flow processes during reservoir production. 4D seismic has all the traditional benefits of 3D seismic, plus a major additional potential benefit that fluid-flow processes can be directly imaged. To first order, seismic images are sensitive to spatial contrasts in two distinct types of reservoir properties:non-time-varying static geology properties such as lithology, porosity, shale content; andtime-varying dynamic fluid-flow properties such as fluid saturation, pore pressure and temperature. Given a single 3D seismic survey, representing a single snapshot in time of the reservoir, the static geology and dynamic fluid-flow contributions to the seismic image are non-uniquely coupled and therefore difficult to separate unambiguously. For example, it may be impossible to distinguish an oil-water contact from a horizontal depositional boundary in a single seismic image. However, with 4D seismic surveys, examining the difference between time-lapse 3D seismic images allows the non-time-varying geologic contributions to cancel, resulting in a direct image of the time-varying changes caused by reservoir fluid flow. For example, an oil-water contact may move with time in a series of time-lapse seismic images, whereas a depositional boundary should not. In this way, the 4D seismic technique has the potential to image, in a large volume encompassing many wellbores, changes in fluid saturation, pore pressure and temperature during production. 4D seismic reservoir monitoring promises to add significant improvements in our ability to estimate saturation and pressure distributions from sparse well control and flow simulations. P. 449^