Development of a Static/Dynamic Model for Chac Field Based on a Novel Multidisciplinary Workflow

Abstract

Abstract The development of advanced computational systems has increased not only the capability but also the demand of complex simulation models in the oil industry. Unfortunately, due to the complexity of naturally fractured reservoirs in the Gulf of Mexico, PEMEXs North-East Marine Region has faced many difficulties in producing these models for its new and mature fields. A practical workflow to generate static-dynamic simulation models for naturally fractured reservoirs is presented, with a strong emphasis on multi-disciplinary integration and interaction. A constant feedback between the various disciplines is crucial for a successful project. The methodology was applied to develop the static-dynamic model for Chac field, located off the coast of Campeche. The simulation model was constructed with 100% active cells. The dimensions of the grid were optimized to maximize efficiency without losing vertical geological definition. The model is able to reproduce the historical pressure-production behavior of the field, as well as the behavior of individual wells. Using coning and channeling correlations for fractured reservoirs; uncertain oil production data of some wells were revised to reproduce observed water productions. The results of this work show how a multidisciplinary approach, during the construction of static and simulation models, creates a synergic environment that strengthens available tools. Additionally, this approach encourages the creation of larger pools of information from different sources and specialties, which can be used to explain reservoir phenomena observed during history matching. This novel methodology, based on an integrated workflow, will allow the optimized construction and history match of numerical models developed for the RMNE. The interaction between various disciplines will provide a better understanding of reservoir phenomena, which in turn, will provide better tools during the decisions making process.