Reservoir Connectivity Evaluation and Upscaled Model Screening Using Streamline Simulation

Abstract

Abstract Significant gas potential has been identified in both conventional and unconventional reservoirs in emerging gas projects in Algeria, south-western Sahara. This study is focused on Lower Devonian reservoirs, which overall depositional model is characterized by shallow marine shelfal to tidal sandstones and mudstones in a range of depositional settings, with thin thickness (less than 10 m) and low porosity and permeability, at 3000–4000 m depth. The analysis of eight exploratory wells drilled in the area, has shown that the field under study presents high lateral and vertical heterogeneity, with an important connectivity uncertainty. Geological models were performed with the objective to evaluate the structural complexity and high reservoir heterogeneity. In order to account for the properties variation uncertainty in the inter-well distribution, and the impact in upscaled models and resulting reservoir simulation, different geological model approaches were evaluated using streamline simulation, concentrating the study on some of the most important parameters that control the number of wells and recovery: reservoir quality, distribution and connectivity. Streamline simulation allowed us to optimize the simulation grid, with the objective to capture the critical reservoir features of the fine-grid geological model. Streamline simulation can be used to analyze and rank different geological models based on certain dynamic performance parameters that effectively reflect the reservoir connectivity, which cannot be easily analyzed with finite difference simulations. The volumetric sweep efficiency and the water cut response can be used to understand the reservoir connection and heterogeneity, and the optimum level of upscaling comparing with fine-grid models. Relatively few real field case examples of this technique have been documented in the past and this paper presents a clear workflow which helped to improve the knowledge of upscaled models screening and resulting reservoir connectivity evaluation.