Saturation Estimation Using mCSEM Data and Stochastic Petrophysical Modeling

摘要

A method for estimating saturation using mCSEM data and stochastic petrophysical models by quantifying the average water saturation in a reservoir given the transverse resistance (TR) obtained from mCSEM data, including the following steps: a) obtaining mCSEM survey data from a subsurface region of interest, b) performing an inversion of the obtained mCSEM data, c) subtracting a background resistivity trend from the mCSEM inversion data from the resistivity trend of the mCSEM inversion data from inside a hydrocarbon reservoir, d) estimating the location of an anomaly in the mCSEM inversion data, e) estimating the magnitude of the transverse resistance associated with an anomaly from the mCSEM inversion data, f) estimating an initial average reservoir saturation corresponding to transverse resistance using a stochastic petrophysical model and Monte Carlo simulation connecting reservoir parameters to transverse resistance, and g) integrating the obtained saturation distribution as a function of transverse resistances over the assumed distribution of transverse resistances to obtain a final estimation of the fluid saturation probability.

主权项

1. A method for the estimation of fluid saturation in a reservoir comprising the flowing steps:
a) obtaining marine controlled-source electromagnetic (mCSEM) survey data from a subsurface region of interest, b) performing an inversion of said obtained mCSEM data to obtain mCSEM inversion data, c) locating an anomaly in the mCSEM inversion data., d) subtracting a background resistivity trend of said mCSEM inversion data from the resistivity trend of said mCSEM inversion data at the anomaly, e) estimating the magnitude of the a transverse resistance associated with the anomaly using the difference from the background resistivity trend, f) estimating a distribution of the average reservoir saturation corresponding to transverse resistance using a stochastic petrophysical model and Monte Carlo simulation connecting reservoir parameters to transverse resistance, and g) integrating the obtained saturation distribution with respect to transverse resistances and weighted by an assumed distribution of the estimated transverse resistances to obtain a final estimation of the fluid saturation probability.