Top-Down Reservoir Modelling
- G.J.J. Williams (BP) | M. Mansfield (BP) | D.G. MacDonald (BP) | M.D. Bush (Consultant)
- Document ID
- Society of Petroleum Engineers
- SPE Annual Technical Conference and Exhibition, 26-29 September, Houston, Texas
- Publication Date
- Document Type
- Conference Paper
- 2004. Society of Petroleum Engineers
- 5.1.1 Exploration, Development, Structural Geology, 5.6.4 Drillstem/Well Testing, 4.1.6 Compressors, Engines and Turbines, 4.3.4 Scale, 5.5.8 History Matching, 5.1 Reservoir Characterisation, 5.6.9 Production Forecasting, 6.5.2 Water use, produced water discharge and disposal, 2 Well Completion, 5.1.5 Geologic Modeling, 5.1.2 Faults and Fracture Characterisation, 5.5 Reservoir Simulation, 4.1.2 Separation and Treating, 5.1.9 Four-Dimensional and Four-Component Seismic, 4.2 Pipelines, Flowlines and Risers, 5.8.7 Carbonate Reservoir, 1.1 Well Planning, 1.6.1 Drilling Operation Management, 5.4.2 Gas Injection Methods, 4.1.5 Processing Equipment, 1.6.9 Coring, Fishing
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Over the last twenty or more years of reservoir performance prediction through simulation there have been only two fundamental changes. First was the evolutionary increase in computing speed that has allowed larger, more detailed reservoir models to be built. Second was the revolutionary change in approach that involved the entire subsurface community in building integrated reservoir descriptions. The next big change may in time prove to be BP's Top-Down Reservoir Modelling (TDRM). This is a new pragmatic approach to fully incorporate reservoir uncertainty in model construction and performance prediction.
TDRM is proprietary technology that has been developed in BP through extensive R&D, and consists of a philosophy and tools that enable a faster and more robust exploration of uncertainty than has hitherto been possible. The philosophy is to start investigations with the simplest possible model and simulator appropriate to the business decision. Detail is added later as required. The approach overcomes the problems of the conventional "bottom-up" process, which uses detailed models that are too slow and cumbersome to fully explore uncertainty and identify critical issues. Highly detailed models cannot overcome an underlying absence of information, and can have the negative effect of creating a false sense of understanding.
The TDRM tools have been designed to minimise manual iterations by creating a semi automated, flexible workflow for case management, assisted history matching, depletion planning optimisation and post-analysis. TDRM has been successfully applied to eighteen oil and gas reservoirs that range from development appraisal stage to mature fields, and has resulted in up to 20% increase in estimated net present value for the projects.
The business imperatives in developing oil and gas reservoirs are faster pace and less risk from subsurface uncertainties. Quantification of the uncertainties is difficult and time consuming because of a) the intrinsic subsurface complexity, requiring integration of data from core to seismic scales (cm to 10's m), b) the sparseness of information requiring estimation of unknown data for the construction of possible geological and simulation models, and c) the need to consider a large number of development scenarios.
Processes used to estimate uncertainties vary, but the general trend is to start by building a large (multi-million cell) geological model. Often the type of model is independent of the business decision, timeframe and amount of data available. Due to the complex workflow and effort, the focus is on building only one, the "most likely", detailed model, even though evidence from the data indicates that there are many possible models.
The next step is to build a simulation model that typically involves upscaling the geological model. If production data exist, this simulation model is history matched manually. Iterative rebuilding of the underpinning geological model is generally avoided. Exploration of the uncertainty in performance prediction using the simulation model is often limited to one-at-a-time sensitivities around a base case. These sensitivities are only a small sample from the factorially combined possibilities. The effort to reach this stage is significant and can be many months for a major reservoir decision.
Overall, the focus of activity has been building ever more complex (hence apparently realistic) models and predicting performance from only a single realisation. Breaking away from this general approach and focusing on the real uncertainty breadth in performance prediction is a conceptual leap which requires new technology and understanding.
Technology improvements are providing better information about current and future reservoir performance and offer the opportunity to quantify the risk from subsurface uncertainties. Some of these advances are highlighted below.
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