Schlumberger Technology Corporation

Metin Karakas

Ian D Bryant

Carlos Torres-Verdin

Min-Yi Chen

David J Rossi

Vladimir L'vovich Druskin

Alberto Malinverno

Sheng Fang

Brian Spies

Methods for locating an oil-water interface in a petroleum reservoir include taking resistivity and pressure measurements over time and interpreting the measurements. The apparatus of the invention includes sensors preferably arranged as distributed arrays. According to a first method, resistivity and pressure measurements are acquired simultaneously during a fall-off test. Resistivity measurements are used to estimate the radius of the water flood front around the injector well based on known local characteristics. The flood front radius and fall-off pressure measurements are used to estimate the mobility ratio. According to a second method, resistivity and pressure measurements are acquired at a variety of times. Prior knowledge about reservoir parameters is quantified in a probability density function (pdf). Applying Bayes' Theorem, prior pdfs are combined with measurement results to obtain posterior pdfs which quantify the accuracy of additional information. As new measurements are acquired, posterior pdfs, updated for expected temporal variations, become prior pdfs for the new measurements. According to a third method, uncertainty about the reservoir parameters is represented by Gaussian pdfs. The relationship between measurements and reservoir parameters is locally approximated by a linear function. Uncertainties are quantified by a posterior covariance matrix.

Methods and apparatus for dynamically estimating the location of an oil-water interface in a petroleum reservoir

Inception of hydrocarbon extraction from a reservoir causes the oil-water interface to warp and cusp toward the extraction gates along a well. This invention proposes time-lapse DC/AC measurements with an array of permanently deployed sensors in order to detect and estimate the change in geometry and proximity of the oil-water interface as a result of production, and therefore as a function of time. The estimation is carried out with a parametric inversion technique whereby the shape of the oil-water interface is assumed to take the form of a three-dimensional surface describable with only a few unknown parameters. A nonlinear optimization technique is used to search for the unknown parameters such that the differences between the measured data and the numerically simulated data are minimized in a least-squares fashion with concomitant hard bound physical constraints on the unknowns. The proposed estimation procedure is robust in the presence of relatively high levels of noise and can therefore be used to anticipate deleterious water breakthroughs, as well as improve the efficiency with which the oil is produced from the reservoir.

Method for sensing and estimating the shape and location of oil-water

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Amstelveen, Netherlands

Metin Karakas