Integrating Multi-Disciplinary Reservoir Description to Characterize Connectivity in a Complex Minibasin Fill: Holstein Field

Wiseman, Terrence R.¹, Roger N. Wagerle², Alex Bump³, Neal F. McCaslin¹, Paulo R. Ballin⁴ (1) BP America Inc, Houston, TX (2) BP America Inc, houston, TX (3) BP America Inc, Houston, TX (4) BP America Inc, Houston, TX

Holstein reservoirs comprise a series of stacked, Lower to Middle Pliocene turbidite sands with the field formed by a large, steep, southeasterly dipping, monoclinal structure with oil column heights exceeding 2500 ft. Stratigraphic and structural complexity is documented through careful intra-reservoir mapping, seismic facies analysis and structural interpretations integrated with static and dynamic pressure data (build-up and interference tests). The integrated geologic analysis revises the existing Holstein geologic model for improved development planning and early production management.

The geological model developed at sanction described the unconsolidated reservoir sands as being deposited in a ponded, intraslope, salt basin dominated by thick, high energy amalgamated reservoirs with internal homogeneity and excellent connectivity. Early performance suggests heterogeneities are more complex then originally envisaged. The reservoir architecture elements comprise sandy sheets and channels that shingle to form reservoir units. Static and dynamic pressure data, build-up tests, and interference tests suggest baffling between geobodies and pressure isolated compartments between some shingles. Post-depositional modification of the reservoir further complicates well performance by removing reservoir entirely or reducing thickness. In addition, a structural overprint creates deformation bands which appear to reduce well productivity through reduction of effective permeability in the structurally steepest segment of the field.

A revised understanding of reservoir heterogeneity calibrated with dynamic data has allowed a greater understanding of variations in well performance. On a field scale the characterizations have been incorporated into a re-build of the reservoir model, which has created greater confidence in the depletion plan to optimize recovery.