QUANTITATIVE METHODS FOR RESERVOIR CHARACTERIZATION AND IMPROVED RECOVERY: APPLICATION TO HEAVY OIL SANDS. A CLOSER LOOK AT FIELD MEASUREMENTS

DINWIDDIE, C. L., cdinwid@clemson.edu, Department of Environmental Engineering and Science, Clemson University, Clemson, SC 29625

Improved prediction of interwell reservoir heterogeneity is needed to improve productivity and to reduce recovery cost for California's heavy oil sands, which contain approximately 2.3 billion barrels of remaining reserves in the Temblor and other formations of the San Joaquin Valley. The proposed investigation involves application of advanced analytical property-distribution methods conditioned to continuous outcrop control for improved reservoir characterization and simulation. Utilizing outcrop data and reservoir data, new models for quantifying property distributions will be developed and tested. The models will be applied to prediction of interwell heterogeneity and to multiphase flow simulation in heavy oil sands of the San Joaquin Valley. The proposed investigation will be performed in collaboration with Chevron Production Company U.S.A. as an industrial partner, and will incorporate geologic and production data from the Temblor Formation in Chevron's West Coalinga Field.

In the proposed research, the nature of the heterogeneity that is present in important property distributions such as porosity and permeability will be related to stratigraphic and structural elements of the geology in outcrops and in the reservoir. Using various deterministic and stochastic approaches, including the properties of non-Gaussian stochastic fractal and universal multi-fractals, we will investigate property distributions and scaling factors for outcrop and reservoir data, and the extent to which these approaches are able to predict interwell heterogeneity.

Laterally continuous outcrops that are depositionally analogous to the heavy oil reservoirs of the San Joaquin Valley will be utilized for performing multiple realizations of property distributions within a well defined sequence stratigraphic framework, and for testing the predictive capability between input control points. The sequence stratigraphic framework provides a consistent hierarchy in which to investigate scale. In our proposed study we will attempt to identify and quantify the physical relationships between the genetic geological processes responsible for reservoir formation and the natural response of scaling.

We propose to assess the hypothesis that non-Gaussian fractals and universal multifractals provide the basis for a new type of geostatistics that is much more compatible with reality by using the continuous outcrop data to develop and test property distribution models. The outcrop-conditioned models will then be applied to reservoir characterization and flow simulation of West Coalinga Field. Successful implementation of the technique at West Coalinga will yield a powerful new approach directly applicable to improved characterization and increased recovery from California heavy oil reservoirs and from other types of reservoirs.

In this presentation we will take a closer look at the principles of operation behind the minipermeameter, which will be utilized in the field to gather permeability data. Additionally, we will examine the appropriateness of typical simplifying assumptions and related sources of error, with the motivation of achieving the best data sets possible.