How can you manage risk in reservoir simulation?

1 Understand the sources of uncertainty

Uncertainty in reservoir simulation can come from various sources, such as data quality and quantity, model assumptions and parameters, numerical methods and algorithms, and human factors. You need to identify and quantify the sources of uncertainty and their impact on the simulation outcomes. You can use techniques such as sensitivity analysis, error analysis, data validation, and quality control to assess the uncertainty and reduce the errors in your data and model.

2 Use probabilistic approaches

Probabilistic approaches are methods that account for the uncertainty and variability in the input data and model parameters by using probability distributions and random sampling. They can help you generate multiple scenarios and outcomes that reflect the range of possible reservoir behaviors and responses. You can use techniques such as Monte Carlo simulation, Bayesian inference, and stochastic optimization to perform probabilistic reservoir simulation and evaluate the risks and opportunities associated with different reservoir management strategies.

3 Incorporate history matching and updating

History matching and updating are processes that adjust the input data and model parameters to match the observed historical data from the reservoir, such as production rates, pressures, and fluid compositions. They can help you improve the consistency and validity of your simulation model and reduce the uncertainty and discrepancy between the model and the reality. You can use techniques such as inverse modeling, data assimilation, and ensemble methods to perform history matching and updating and update your simulation model as new data becomes available.

4 Apply validation and verification

Validation and verification are procedures that check the quality and performance of your simulation model and ensure that it meets the objectives and requirements of your reservoir project. Validation is the process of comparing the simulation results with independent data or criteria to evaluate how well the model represents the real system. Verification is the process of testing the simulation model for errors, bugs, or inconsistencies in the code, logic, or implementation. You can use techniques such as cross-validation, benchmarking, and debugging to apply validation and verification and ensure that your simulation model is accurate and reliable.

5 Communicate and document the results

Communication and documentation are essential steps to present and share the results of your reservoir simulation with your stakeholders, such as managers, clients, or regulators. They can help you explain the assumptions, methods, limitations, and uncertainties of your simulation model and how they affect the results and recommendations. You can use techniques such as visualization, reporting, and archiving to communicate and document the results of your reservoir simulation and support your decision-making and risk management processes.