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Publication Date: 2010-Dec-17
Document File: 4 page(s) / 55K

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The methods and systems described herein are directed at using graphics processing units (GPU) to accelerate the prediction of in-situ formation petrophysical properties from downhole logging measurements and/or geological information. The formation properties include at least those not measured directly from downhole logging measurements, such as absolute permeability, relative permeability, resistivity formation factor and index, capillary pressure, mechanical properties, and so on. In one aspect, computational methods used to derive these properties from an earth formation model are implemented on a GPU-based architecture to achieve dramatic computational performance gain as compared to those using just the central processing unit (CPU). The numerical methods implemented on the GPU include at least those calculating the properties mentioned above, such as the pore network model, lattice Boltzmann flow simulation, finite difference method and finite element method. In another aspect, the formation model provided to the GPU is a three-dimensional digital rock sample reconstructed from downhole logging measurements and/or geological information. The model represents the earth formation at a given depth, and accounts for different rock-forming diagenetic processes such as sedimentation, compaction, and precipitation or dissolution of carbonate and clay minerals. Algorithms related to model reconstruction are also implemented on a GPU platform to utilize the high computational performance of GPU.

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Record Number: 5006 Invention Infoview Form


BHI File Number: Product Line: *

TLE4-51198-US D&E2 - Wireline
Date Started :08/04/2010

Technology: *
(PLG) Prod. Logging/DH Completion
Title of Invention:
Accelerating Formation Petrophysical Property Prediction From Log-Derived Rock Models Using GPU

Abstract of the Invention: Market Segment: Market


This invention is directed towards the use of modeling methods that enable the

construction of a representative formation rock model from downhole logging

measurements and geological information, and the use of graphics processing units (GPU)

to accelerate the calculation of rock properties from the model that are not measured by

the formation evaluation logging tools. The combination of rock modeling approaches and

GPU implementation allows to predict quickly (within one or several minutes) and

accurately petrophysical properties (e.g., permeability, relative permeability, resistivity

formation factor, and capillary pressure) directly from downhole logging measurements.

Product/Service Name (if known):

Formation evaluation


FirstName LastName MiddleName CostCenter EmployeeNumber WorkEmail Status

Guodong Jin 410300613 00128376 Approved

Sergey Martakov 410300613 00117067 Approved

Non BHI Employee Inventor(s):


1. Describe the invention in detail. Describe the preferred manner of practicing the invention including listing the steps, method,

composition and operation of the invention. Point out features that are believed to be new and how the invention overcomes the

disadvantages of the old manner. Attach electronic documents such as sketches, drawings, photographs, logs, etc., as needed.

Non-electronic documents must be sent to the Legal Department representatives. * In-situ formation petrophysical properties are of

great importance in the petroleum industry not only to evaluate reservoir potential, but also to support drilling strategies in terms of borehole

stability, completion decisions related to sand production, as well as the potential for hydraulic fracturing and perforation. Some properties,

such as permeability, relative permeability, resistivity formation factor, and capillary pressure, are very difficult, if not impossible, to measure

directly using current sub-surface logging technology. Traditional laboratory measurements are often costly, time-consuming and require

large amounts of core materials that may not always be available at the time when drilling and completion decision have to be made.

Numerical techniques currently used, which rely on as an input the micro-CT images (require a core sample) or generated numerical rock

models (need information obtained on a thin section made either from a reservoir core plug, wall cores or drill cuttings), also demand large

computational resources (memory and time) and require days...