Reconciling Prior Geologic Information With Production Data Using Streamlines: Application to a Giant Middle-Eastern Oil Field
- Darryl Hyde Fenwick (Streamsim Technologies, Inc.) | Marco Roberto Thiele (StreamSim Technologies, Inc.) | Mohammed Alawi Agil (Saudi Aramco) | Ahmed Hussain (Saudi Arabian Oil Company) | Fahad A. Al-Humam (Saudi Aramco) | Jef Karel Caers (Stanford University)
- Document ID
- Society of Petroleum Engineers
- SPE Annual Technical Conference and Exhibition, 9-12 October, Dallas, Texas
- Publication Date
- Document Type
- Conference Paper
- 2005. Society of Petroleum Engineers
- 5.8.6 Naturally Fractured Reservoir, 5.5 Reservoir Simulation, 4.3.4 Scale, 4.1.5 Processing Equipment, 5.1.5 Geologic Modeling, 5.5.8 History Matching, 5.8.7 Carbonate Reservoir, 4.1.2 Separation and Treating, 7.6.2 Data Integration, 5.5.7 Streamline Simulation, 5.1.7 Seismic Processing and Interpretation
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Effective history matching of real fields requires the resolution of two outstanding problems.First, a conflict may exist between the production data and the existing geological model built solely from static information.In resolving this problem one must relate the inherent multi-scale nature of production data to petrophysical properties of the reservoir at the proper scale.Second, during model updates, geological consistency must be maintained by honoring the prior geologic information.The geoscientist has to choose what prior information is well know (hence fixed), and what is uncertain (hence modifiable).In many instances, the type of geostatistical algorithm is fixed, while key prior geostatistical parameters should be perturbed (e.g. facies proportions, petrophysical properties trends, variogram parameters, and random seed).
We propose a new methodology that addresses these problems.First, streamlines are used to relate the production data to petrophysical properties at multiple scales.A combination of geostatistical tools (locally varying mean and probability perturbation method) are then used to jointly map multi-scale corrections back to the geological model through changes of the prior geostatistical parameters.The mapping reconciles the fixed prior geologic information with the production data.The geological model is then explicitly recreated by re-running the geostatistical simulation.This approach differs from other history matching techniques where the petrophysical properties of each grid block are modified directly.While a successful history match may be obtained, the resulting model may be inconsistent with important prior information, hence retaining little predictive power.
The methodology is demonstrated by applying it to history matching a giant Saudi Arabian carbonate oil reservoir. This reservoir has over 500 producers and over 50 years of historical data with dramatically changing field conditions. In the past, several attempts were made to manually history matching this reservoir. The process was found to be extremely time consuming, involving dramatic local permeability changes which are often not supported by geological data. By applying the new approach, rather than correcting permeability manually, the corrections supplied by the streamlines were used to constrain the geostatistical algorithms, thereby ensuring a consistent geological scenario at every iteration.
Streamline-based history matching has been a subject of intensive research over the last several years (see, for example Refs. 2-9).History matching using streamlines has been shown to be an attractive alternative to traditional history matching when streamline simulation is applicable.All streamline-based history matching methods take advantage of the simple relationship between the time-of-flight of the streamline (t), and the effective porosity (F) and effective permeability (k) of the streamline.The time of flight is defined as,
This relationship was first derived by Pollack.The time-of-flight is described as the time required for a neutral particle to follow the total velocity field (vt) from source to sink (along streamline path ?).The path that the particle traverses traces the path of the streamline.Since the total velocity of the fluids is directly proportional to the effective permeability along the streamline, we know that
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