The objectives of the project are to improve reservoir management and maximize oil recoveries by understanding and quantifying reservoir uncertainty and to improve the capabilities of DOE’s BOAST II software by incorporating probabilistic module in the simulator.
Advanced Resources International, Inc. (ARI)
Reservoir simulation is a powerful tool in predicting reservoir performance. However, the prediction is not unique, due to inherent uncertainty in the input data as well as in the solution method employed by the simulator. Finite-difference simulation coupled with probabilistic methods offers the best possible tool to predict production profiles, given a wide variety of assumptions about reservoir character and predicting conditions. Monte Carlo analysis has been successfully applied in the industry primarily for reserve estimations. Few investigators have applied this technique to finite-difference simulation, however.
Commercially available simulators do not have probabilistic tools working in an integrated fashion. The Monte Carlo technique was used to independently create several hundreds of combinations of uncertain reservoir parameters, and finite-difference simulations were performed for each of these realizations. The complexity of this procedure prohibited the user from using probabilistic models for reservoir predictions. Additionally, small independent companies are particularly constrained from performing detailed simulation studies due to smaller technical staffs and resources.
All of the project work has been completed. The VB interface, which is the main user interface and interacts with all the other components of the application, has been completed. The Excel application that contains the computational steps for generating probabilistic models of reservoir parameters is completed. The Monte Carlo simulation process is incorporated in the Excel application. Additionally, the development of the MS Access database for storing and reviewing simulation results is completed.
The new application has the capability to generate probability distributions for most of the BOAST II input parameters and then automatically run thousands of simulation cases. With the output of the simulation runs stored in MS Access database, the results can be analyzed using plots, such as a tornado plot, to identify input parameters with the highest influence on the output parameters. Finally, the goodness-of-fit computations can be made between simulated and historical data to assist the history-matching process.
The new tool integrates reservoir simulation with probabilistic (Monte Carlo) simulation, whereby thousands of realizations of reservoir output can be generated automatically with the probabilistic distribution of input parameters. This capability will greatly help simulation engineers in history-matching reservoir production data. Further, important drivers of production performance and reserves can be readily identified, providing operators with an understanding of where their technical uncertainty and risk exists. Moreover, future production forecasts can be performed probabilistically, thus providing better understanding of reserve yields and potential upsides and downsides.
This project was awarded to develop a user-friendly, PC-based interface that integrates DOE’s free BOAST II simulator with the Monte Carlo simulation technique. The new application can generate probability distributions for most BOAST II input parameters and then automatically run thousands of simulation cases. The output of the simulation runs is stored in an MS Access database for analysis.
The project has achieved most of it goals. Project researchers have:
All of the work has been completed for the project.
$52,280 (20% of total)