Integrated Reservoir Characterization

Sanjay Srinivasan ( is the Program Manager of the Integrated Reservoir Characterization research program.

The focus of the Integrated Reservoir Characterization program is on:

  • Providing practical approaches for assessing and managing geologic and flow related uncertainty using improved physical and stochastic models

  • Providing insights into the physics of fluid flow through multi-scale heterogeneous media

Announcement: Short Course and Workshop on Image Analysis for Porous Media Scheduled for July 12-15, 2011

Co-organized by Masa Prodanovic

Imaging of porous materials, as well as the changes due to various process such as flow within their voids or exposure to external stress, is becoming a ubiquitous method of material characterization as well as simulation validation. We've organized two events with this important focus:

  • The short course will provide graduate students and researchers with basic training in image analysis for porous media.
  • The workshop will present an overview of the latest advances in image analysis, characterization and related modeling of porous media.

Please see the Short Course and Workshop on Image Analysis for Porous Media information page for details.

Curent DOE Research

Mukul M. Sharma, Carlos Torres-Verdin, Steven L. Byant (in collaboration with Professor George Hirasaki at Rice Unversity) (

Funding amount: $800,000 for the period of Oct. 2004 - Sep. 2007

This research will use advanced dielectric and NMR measurements to understand and predict the flow of oil and water in reservoir rocks. Such improved characterization methods are vital for the continued production from existing domestic oil reservoirs at low cost and high efficiency.

Jerry Jensen (Texas A&M University), Larry W. Lake (

Funding amount: $179,000 for the period of Sept. 2003 - Aug. 2006

This work aims to develop a new approach to evaluating the flow paths between injection and production wells. The procedure will use injection and production rates and target three different production scenarios: fields with wells shut in for extended periods; fields with non-uniform compressibility; and very heterogeneous reservoirs.

Other Research Projects

Larry W. Lake

The exploration and production industry has had a long history of purely statistical models, though this practice has almost entirely given way to the algorithmic models now referred to as numerical simulators. On the other end of the spectrum the ultimate simplification will be a simple model that does empirically quantifies the flow physics in the form of simple to evaluate statistical correlation(s).

Jon E. Olson

Predicting the performance of fractured reservoirs requires characterization of fracture length, spacing, height and aperture distributions.  Because none of these parameters are typically well constrained by available subsurface data because of small sample size (wellbores) or indirectness of the measurement (seismic), theoretical models are required to fully populate fracture networks for flow simulation.

The approach consists of developing a digital repository of reservoir models classified on the basis of reservoir depositional environments. These analog reservoir models will be constructed using rock outcrop data interpreted by expert geologists.

Graduate Research Assistant: Harpreet Singh
Principal Investigator: Larry Lake

The objective of this work is to develop integrated decision and risk analysis, involving reservoir modeling (static and flow) starting from well or seismic data and applying economic analysis procedure using Real Options Valuation.

Steven L. Bryant
Collaborators: Todd Arbogast (Dept. of Mathematics and Center for Subsurface Modeling) and Jim Jennings (Bureau of Economic Geology)

Vuggy rocks like the one pictured below right present a challenge to traditional models of flow and transport in porous media. In this formation, the vug lengths are 10s of cm, too big for standard core analysis to capture. This research project is seeking to model large scale behavior (effective permeability, contaminant transport) from fine-scale models that account for the geometry of the vugs and the matrix surrounding them.

Graduate student: Brian Lee
Principal Investigator: Larry Lake

The goal of the project is to develop a probabilistic graphical model that, when given some properties of the reservoir, produces a predicted value of recovery factor. The fundamental mechanics behind this process is described as Bayes’ updating applied to a chain of variables, each with its own probability distribution.