2001 05 29
Modeling Natural Fracture Networks Using Coupled Multi-Point Geostatistics and Flow Simulation
Presentation - ppt. (1,043KB) 

Nexen Inc. and the University of Calgary invite you to attend an information session on the newly created Center for the Advancement of Geostatistics in Engineering (CAGE).   A major component of CAGE's research and development effort is to investigate methods for characterizing and modeling natural fractures. 
 

Date:       Tuesday, May 29, 2001
Time:       12:00 – 2:00 PM (lunch provided) 
Location: PanCanadian Amphitheatre, Room 260, Tower Centre, 2nd Level
                131-9th Ave. SE, Calgary, AB

Background
CAGE has acquired a workstation network with 8 gigabytes of high-speed memory.  The system's low-speed memory is expandable to over 1 terrabyte.  Recent time trials running reservoir simulations requiring over 2 gigabytes of high-speed memory (approx. 2 million grid cells) ran approximately 5 times faster than a super-cluster system at another well-known, U.S. educational institution.  ).   A major component of CAGE's research and development effort is to investigate methods for characterizing and modeling natural fractures.

Project Description
Natural fractures act as major heterogeneities that control flow of hydrocarbons in almost 30% of the world’s hydrocarbon reservoirs. Fracture transmissivity (or permeability) can enhance oil production and result in early water breakthrough and subsequently early well abandonment. A key aspect of forecasting fluid production from fractured reservoirs is the characterization of fracture flow paths. The fracture density, as well as connectivity, influences the reservoir flow performance. However, exact spatial characteristics of the fracture system have not been determined for the subsurface reservoir. Instead, statistical characterization of fracture systems is usually attempted.

We are developing a new, breakthrough technology to model the behavior of natural fractures in forward or inverse simulations (within a particular fracture network density and orientation which can be established from outcrop and seismic data).  In the forward case, we will determine the reservoir response.  In the inverse case, for a particular reservoir response, we will determine the fracture network density and orientation.  To achieve this, a new, powerful, numerical and geostatistical flow model has been developed.  The output, in the forward case, will be a range of probable pressure and flow distributions in the reservoir and, in the inverse case, a range of probable fracture network characteristics for a given reservoir production and pressure history. 

To register or to obtain technical information: Dale Wong via Phone: (403) 701-8277 email: dalwong@ucalgary.ca no later than May 25, 2001.

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