Feasibility of using full tensor gradient (FTG) data for detection of local lateral density contrasts during reservoir monitoring

被引:23
作者
Droujinine, Alexander
Vasilevsky, Alexander
Evans, Russ
机构
[1] British Geol Survey, Edinburgh EH9 3LA, Midlothian, Scotland
[2] Inst Geol, Novosibirsk 630090, Russia
[3] Shell Int Explorat & Prod BV, NL-2288 GS Rijswijk, Netherlands
关键词
FTG; regularized inversion; reservoir monitoring;
D O I
10.1111/j.1365-246X.2007.02806.x
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Three-Dimensional Full Tensor Gradiometry (3-D FTG) acquires ultrasensitive measurements of the Earth's (vector) gravity gradient field. Departures from simple weakening of the field in the vertical direction are due to subsurface variations in density. We have undertaken a numerical examination of the feasibility of using this system for detecting time variations in local lateral density contrasts in subsurface layers during reservoir production monitoring. Our gravity modelling focuses on the value added by taking account of the horizontal components of gravity gradient in imaging local targets. We have studied the sensitivity of these components to model and acquisition parameters. Iterative regularized inversion algorithms that can explain the behaviour of a hydrocarbon reservoir in terms of time-lapse density changes have been described. These algorithms are based on the homotopy method that utilizes the solution space topology. To stabilize the inversion, we have introduced the maximum compactness of anomalous sources along one or more directions. This allows the use of a priori information natural to time-lapse monitoring about the arbitrary shape and spatial locations of the sources. The time-evolving density contrast within the local target zone is recovered by means of an iterative procedure. The treatment of either correlated or random noise fits naturally into this procedure. The final scheme has been illustrated by several examples using synthetic FTG data generated from various density distributions of practical interest. We have considered the effect of model and data uncertainties on the inversion solution. It appears that the iterative process is effective, numerically stable and rapidly convergent in the presence of both random and structural noise. Results show that it is relatively insensitive to the choice of starting model. Appropriate applications include direct monitoring of gas-oil contact and temperature front expansion during steam injection in heavy-oil reservoirs at shallow or moderate depths.
引用
收藏
页码:795 / 820
页数:26
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