Generating facies probablity cubes

Abstract

A method for generating one or more geological models for oil field exploration. The method includes receiving one or more well facies logs, a vertical facies proportion curve, a lateral proportion map, a variogram model and a global target histogram. The method then includes generating a facies probability cube using a modified Sequential Gaussian Simulation (SGSIM) algorithm, the well facies logs, the vertical facies proportion curve, the lateral proportion map and the variogram model. After generating the facies probability cube, the method includes matching the facies probability cube to the global histogram and generating the geological models based on the matched facies probability cube.

Description

RELATED APPLICATIONS[0001]This application is a continuation of and claims priority to U.S. patent application Ser. No. 12 / 837,936 filed 16 Jul. 2010, titled GENERATING FACIES PROBABILITY CUBES, which in turn claims priority to U.S. provisional patent application Ser. No. 61 / 315,098 filed Mar. 18, 2010, titled METHOD FOR RESERVOIR MODELING USING A GEOSTATISTICAL APPROACH TO GENERATE 3D PROBABILITY CUBES OF BINARY FACIES WITH GEOLOGICAL CONSTRAINT, both of which are incorporated herein by reference.BACKGROUND[0002]1. Field of the Invention[0003]Implementations of various technologies described herein generally relate to techniques for modeling geological properties of the earth and, more particularly, to techniques for generating facies probability cubes that can be used with multipoint statistics to create a reservoir model.[0004]2. Description of the Related Art[0005]The following descriptions and examples are not admitted to be prior art by virtue of their inclusion within this se...

AI Technical Summary

Problems solved by technology

Soft data are not as accurate as hard data but typically have larger or better coverage of the reservoir.

The pixel-based approach provides increased flexibility for constraining the model according to reservoir data but it often has poor shape reproduction in the final reservoir models.

In contrast, the object-based approach tends to generate more realistic shapes of geobodies; however, it becomes more difficult to constrain the models according to local reservoir observations, particularly when there are dense well locations.

However, automatically generating facies probability cubes that are geologically sound remains a challenge.

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