Incorporating uncertainty into geological and flow simulation modelling in Chevron:: application to Mafumeira, a pre-development field, Offshore Angola
Published:January 01, 2008
A. Chakravarty, A. W. Harding, R. Scamman, 2008. "Incorporating uncertainty into geological and flow simulation modelling in Chevron:: application to Mafumeira, a pre-development field, Offshore Angola", The Future of Geological Modelling in Hydrocarbon Development, A. Robinson, P. Griffiths, J. Price, J. Hegre, A. Muggeridge
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In this paper, we describe a reservoir-modelling case history of Mafumeira, a Chevron-operated field located in Offshore Angola. The field has only six well penetrations and lies within the closure of nearly 60 square kilometres; the purpose of the study was to capture a range of subsurface uncertainties for evaluation of the development options. We used a Depositional Facies Modelling scheme utilizing recent developments in Multiple Point Geostatistical Simulation and reservoir property uncertainty analysis to generate five static reservoir models. After scale-up, flow simulations were conducted on each model for different field development options using a Design of Experiments (DoE) methodology and a preferred development option was selected.
The geology of Mafumeira field is complex. The multiple point geostatistical simulation used a training image consisting of seven depositional facies. The training image is a 3D conceptual model of the facies present and the facies associations; it captures complex spatial relationships between multiple facies, and non-linear shapes such as sinuous channels. The facies simulation was conditioned by a facies probability cube, which permitted the use of a single training image for different stratigraphic intervals of the reservoir, with different combinations and proportions of the seven facies. Multiple versions of the facies probability cube were produced to model the uncertainty in the occurrence of reservoir quality rock units.
In modelling the reservoir properties, uncertainties in porosity, permeability and water saturation (‘PKS’) were taken into account. Five models were produced reflecting the combinations of high- and low-case reservoir facies, high- and low-case PKS properties and an intermediate-case. The high-, intermediate- and low-case models were then dynamically tested to ensure different flow behaviours, prior to upscaling, and the flow behaviours compared to analogue producing fields.
In order to utilize DoE simulation, upscaling of the five fine-grid models was required. Flow-based simulation was chosen as the best tool to validate the behaviour of the coarse-grid models against the fine-grid models. However, this effort demonstrated that the conventional scale-up methods utilized in other reservoir models did not adequately capture the behaviour of the fine-grid models in this heterogeneous reservoir. A new method that adjusts the Dykstra–Parsons coefficient was investigated and successfully employed to tune the coarse-scale models.
Twelve development alternatives for the field were defined and deterministic economics, based on results from the mid-case simulation model, were run in order to narrow down the number of alternatives to be carried forward into probabilistic analysis to five. The DoE approach allowed us to undertake a thorough evaluation of the key subsurface uncertainties and design an overall development plan. The probabilistic simulation results along with full Decision Analysis (DA) allowed us to identify a phased development, which would mitigate potential downside risks while preserving the ability to capture upside potential.
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The Future of Geological Modelling in Hydrocarbon Development
The 3D geological model is still regarded as one of the newest and most innovative tools for reservoir management purposes. The computer modelling of structures, rock properties and fluid flow in hydrocarbon reservoirs has evolved from a specialist activity to part of the standard desktop toolkit. The application of these techniques has allowed all disciplines of the subsurface team to collaborate in a common workspace. In today’s asset teams, the role of the geological model in hydrocarbon development planning is key and will be for some time ahead.
The challenges that face the geologists and engineers will be to provide more seamless interaction between static and dynamic models. This interaction requires the development of conventional and unconventional modelling algorithms and methodologies in order to provide more risk-assessed scenarios, thus enabling geologists and engineers to better understand and capture inherent uncertainties at each aspect of the geological model’s life.