SULLIVAN, MORGAN, LINCOLN FOREMAN, DAVID JENNETTE, and DAVID STERN, Exxon Production Research Company, AARON LIESCH, Exxon Upstream Development Company,TIM GARFIELD, Exxon Exploration Company

Abstract: Application of Deepwater Outcrop Analog Data to 3-D Reservoir Modeling: An Example from the Diana Field, Western Gulf of Mexico

The challenge at Diana field was to predict the production performance of a channelized deepwater reservoir with a relatively thin oil rim, and a large gas cap.Associated development costs are high requiring an optimization program to ensure a viable project. These predictions were further challenged by variable quality seismic data, a reservoir thickness expressed by a single cycle seismic event, only limited appraisal wells, and the likelihood for sub-seismic reservoir variability that could control the economic viability of the project. To assist with reserve assessments and optimization of depletion strategies, deepwater outcrop analog data were integrated with seismic and well data to produce a detailed object-based model for more accurate reservoir characterization.

The Diana field is situated in the western Gulf of Mexico 160 miles south of Galveston in approximately 4700 ft of water. Diana is the second largest of several discoveries recently made in the Diana Basin and has in excess of 100 MOEB of recoverable hydrocarbons from the Upper Pliocene A-50 reservoir. The turbiditic sandstones and mudstones that comprise the A-50 reservoir at the Diana field were deposited as a lowstand fan within an intraslope basin setting. The field is located on the east flank of a north-south trending salt-cored ridge. Hydrocarbons are trapped by a combination of structure and stratigraphic onlap, with a large gas cap (>1,000 ft column height) and a relatively thin oil column (approximately 240 ft column height).

Based on detailed analysis, the 3-D seismic data at Diana field appears to be of variable quality and does not allow direct geometric analysis of reservoir elements. Qualitative examination of vertical seismic in-lines and cross-lines, however, provides valuable information concerning the architecture of the reservoir elements. Although the seismic data is of variable quality and the reservoir is only expressed by a single cycle seismic event, the excellent core coverage enables close calibration of seismic and well data. The up-dip portion of the A-50 reservoir (Diana 2/Diana 3) is represented by a high amplitude continuous seismic character (Figure la) dominated by amalgamated high concentration turbidites suggesting a relatively channelized depositional setting. The medial portion of the A-50 reservoir (Diana 1) is represented by high amplitude semi-continuous seismic character dominated by nonamalgamated, high-concentration turbidites suggesting a less channelized and more sheet-like depositional setting with limited axial (amalgamated) reservoir elements. Integration of seismic and well data therefore suggests a more channelized reservoir up-dip, becoming more distributive and sheet-like down-dip.This subsurface data, however, did not have the resolution to provide the dimensional and architectural data required to condition a geologic model for flow simulation and well-performance prediction.To solve these uncertainties outcrop analog data from analogous deepwater outcrops were integrated with seismic and well data from the Diana field to provide geometric and architectural data below the resolution of the seismic data.

Outcrops span a critical gap in both scale and resolution between seismic and well-bore data and integration of Diana specific seismic, well-log, core and appropriate outcrop analogs provided the detailed geometric properties required for interpreting the reservoir architecture at a sub-seismic or flow unit scale (Figures lb & 1c).The Lower Permian Skoorsteenberg.Formation in Tanqua Karoo Basin, South Africa and the Lower Carboniferous Ross Sandstone in the Clare Basin, western Ireland are both composed of stacked turbiditic sandstones and mudstones deposited within a channelized basin-floor fan setting. These laterally continuous outcrops provide an excellent opportunity to characterize detailed bed-scale reservoir architecture and internal heterogenities that affect the producibility of deepwater sandbodies in both depositional strike and dip perspectives. In summary, proximal fan deposits are dominated by narrow, amalgamated channels, medial fan deposits are comprised of semi-amalgamated sheets and distal fan deposits are dominated by non-amalgamated sheets, similar to the interpreted up-dip to down-dip architecture of the A-50 reservoir at Diana. Channel and bed scale reservoir architectures were quantified with photomosaics and by correlation of closely spaced measured sections from a variety of channel types to condition the model. Dimensional and architectural data from these outcrops were compared to Diana specific seismic and well data and adjusted accordingly. From these measurements a spectrum of channel dimensions and shapes were collected to condition the modeled objects. In additional to the collection of channel dimensions and shapes, bed continuity, and lateral and vertical facies variability data were collected from a variety of channel types to condition the reservoir model as these factors ultimately control the reservoir behavior.

Object-based models consist of discrete objects (facies bodies) each with specific dimensions, facies juxtapositions and continuity that incorporates geologic interpretation and honors all available data. In the Diana model, the reservoir is represented by a series of stacked channel bodies that are meant to represent deepwater channels. Individual channels are narrow up-dip and become wider and less amalgamated down-dip, as suggested by the integration of the seismic, well-log, core and analog outcrop data. Modeled channels are divided into proximal, medial and distal regions with their own specific set of characteristics. Channels are further subdivided into axis, offaxis and margin associations. Each facies and sub-facies body was then populated with petrophysical properties using Gaussian simulation drawn from sub-facies property histograms generated from available well data. Facies bodies dimensions, architecture and facies proportions were generated from the integration of subsurface and outcrop data.

The ultimate goal of this integrated analysis was to predict architectural controls on the producibility of the relatively thin, yet economically important oil rim which following the discovery at Hoover became economically viable. Based on this modeling effort and flow simulation, significant variations in reservoir performance exist from up-dip to down-dip. The up-dip portion of the reservoir has higher initial oil saturations due to its higher porosities and also starts making high water cuts earlier than the down-dip portion of the reservoir due to its more amalgamated nature and better reservoir quality. This therefore predicts that significant variations in reservoir producibilty exists from up-dip to down-dip and these varying characteristics must be considered in the final development plan.This effort provides the framework for optimal placement of wells to maximize the architectural and facies controls on reservoir performance.

AAPG Search and Discovery Article #90923@1999 International Conference and Exhibition, Birmingham, England