Uncertainty Evaluation in Emerging Gas Projects in North Africa Using Geological Modeling, Reservoir Simulation and Experimental Design

In this study the main uncertainties affecting the reserves estimation in the low permeability Lower Devonian gas reservoirs of an exploration block in Algeria are evaluated. This large gas project faces significant uncertainties as a result of the ambiguities in reservoir quality, architecture and well performance. Therefore, a comprehensive risk analysis is essential to manage the production forecast and the surface facilities sizing evaluation.

Although there have been important advances in terms of reservoir modeling and simulation, the reserves risk analysis remains as a challenging task in the early exploration phase of large projects. Traditional studies commonly use only one geological model for the simulation (P₅₀ or mean case), and the uncertainties are evaluated using a one-parameter-at-a-time approach assuming no dependency among them. Finally, this unique case is adopted to take decisions based on the economic output results analysis and the project commitments.

An alternative to the traditional evaluation is the use of Experimental Design (ED). An analytical equation ("response surface model") is created and this surrogate model is used to study the interaction of all variables and their impact on the simulations. The experimental design coupled with multivariable regression and Monte Carlo simulation could be used for final parameters evaluation. Relatively few real case examples of this technique have been documented, and commonly these applications do not integrate multiple deterministic geological models.

In this paper we present an example of how static and dynamic uncertainties were integrated using a scenario-based approach and ED, building the models and concentrating the study on the variables that control the recovery: reservoir quality, distribution and connectivity, porosity, permeability and fluid contacts. This work helped to quantify the uncertainty for reserves, number of wells and gas rate deliverability estimation, adding significant value to the current field development plan assessment.