A new breakthrough in reservoir modeling is using Training Images (TI) with Multiple Point Statistics (MPS). A TI is a structural image of a reservoir layer or stratigraphic time interval, which represents all the relevant events (e.g. facies) at a time independently from a real location. Therefore, the TI's capsulate much broad geological sense with conceptual patterns or multiple joint relations beyond the traditional geostatistics where it may merely offer two-point correlations (e.g. variograms) with sparse well data.
Each time sequence presents a transgression within Arabian plate along hundreds of km's distance length one would not see the whole sequence of a platform (e.g. lagoon, ramp and shoal deposits) through a relatively small reservoir area (30km x 30 km). This brings a common challenge in facies modeling of carbonate reservoirs regarding lateral changes in deposition settings that are rarely crossed along the small scale reservoir sequences although a diversity of facies types can be observed vertically.
The Arabian Gulf plate reservoir of Lower Thamama around Abu Dhabi was studied to understand how a relatively limited reservoir area was deposited through the help of TI's. A rock-type study based on core and log data was compiled, and 23 facies types varying vertically were identified. TI's were drawn for each time interval between high resolution sequence stratigraphy (HRSS) picks. It was not eligible to drive properties through seismic attributes since the seismic attributes were weak for tuning the facies heterogeneity. The analogs, representing the depositional strata sketch were mapped with outcrop data, core descriptions and solid geological knowledge of the reservoir. Given these conceptual images conditionally, all possible scenarios of the deposition were simulated with MPS algorithms. Uncertainty analysis was also performed to infer the variability of the different TI's.
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AbstractA Geological Model was built and an Uncertainty Assessment approach was used to better understand the reservoir behaviour. Conceptual models were used to constrain the number of realizations, all of which are equi-probable solutions that honour both hard and soft data.Ranking of models was done by progressively analyzing the cases/ scenarios considered. Initially, inconsistent scenarios/ cases were discarded. In other words, those that did not comply with the data distribution expected and/or the spatial distribution and consistency with the conceptual geological models are discarded. The weight of each criterion in the decision that leads to abandon a particular case or scenario varies according to the variable modeled.The final phase involved ranking the different models using body connectivity and volumetrics. The ranking was divided in sets where one variable was considered and others added progressively until all the variables were taken into account, including structure and fluid contacts uncertainty. The selected scenarios were then dynamically evaluated for well and development placement.
TX 75083-3836, U.S.A., fax 01-972-952-9435.
AbstractThe objective of this paper is to present the use of real-time image interpretation during an intensive drilling campaign of horizontal wells in two major carbonate fields onshore Abu Dhabi.
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