R R SPWLA 50 th Annual Logging Symposium, June 21-24, 2009 1 REAL-TIME INTEGRATION OF RESERVOIR MODELING AND FORMATION TESTING Adriaan GISOLF, Francois X. DUBOST Julian ZUO, Schlumberger, Stephen WILLIAMS, StatoilHydro ASA, Julianne KRISTOFFERSEN, Vladislav ACHOUROV, Andrawiss BISARAH, Oliver C. MULLINS Schlumberger Society of Petrophysicists and Well Log Analysts Copyright 2009, held jointly by the Society of Petrophysicists and Well Log Analysts (SPWLA) and the submitting authors. This paper was prepared for presentation at the SPWLA 50 th Annual Logging Symposium held in The Woodlands, Texas, United States, June 21-24, 2009. ABSTRACT The increasing complexities of newly discovered reservoirs coupled with the increasing cost of field development mandate significantly improved and timely work flows for reservoir evaluation. Traditional modeling workflows are typically time consuming and require well-organized cross-disciplinary integration between geoscientists. Such models and processes are not well suited to be used and updated during formation-evaluation acquisition phases of field development. In this paper, a more accessible approach is proposed and demonstrated. The existing fluids model is combined with the current geologic model to construct an accurate representation of key features of the reservoir. This model is then used to predict data for a wireline formation sampling and testing tool (WFT), with emphasis on downhole fluid analysis (DFA). In this process, current reservoir understanding is tested by direct measurement in real time. If differences are uncovered between predicted and measured log data, the WFT tool is in the well, and measurements can be made to uncover the source of the error. In this paper a workflow is demonstrated in which WFT DFA and pressure/volume/temperature (PVT) lab reports were used to build a fluid model after the first exploration well data was acquired. This model was then used to predict fluid properties and WFT DFA logs for a subsequent well intersecting nominally the same compartment. These DFA predictions presumed fluid equilibrium and flow connectivity. Real-time comparisons were made of predicted and measured pressures, fluid gradients, contacts and DFA data obtained from the WFT logging run. Agreement of predicted and measured log data indicates that fluid properties and reservoir connectivities used for the modeling are correct. If predictions disagree with measurements, the acquisition program can be altered in real time to ensure sufficient data are acquired to understand the reservoir model inaccuracies. During the WFT logging job, this predictive model enabled validation of critical WFT data. This process also allowed testing of the reservoir connectivity. It was discovered that either compartmentalization or lateral disequilibrium of the fluids in the reservoir exists. Interpretation of the DFA data suggested that a subtle lateral disequilibrium exists, and the assumption of reservoir connectivity is supported. INTRODUCTION As the search for hydrocarbons goes deeper and into more challenging reservoirs, greater reservoir complexity must be addressed. To properly evaluate such reservoirs continuously challenges formation- evaluation technology and techniques as well as economic limitations. It is essential to improve efficiency in this evolving setting. The existing workflows in reservoir evaluation offer opportunities for improvement. One area of potential improvement is identification of compartmentalization.[Mullins 2008, Mullins 2005, Elshahawi 2006, Elshahawi 2005] The extent of reservoir compartmentalization has a direct impact on the number of wells and the geometry and completion of those wells required to drain a reservoir, thereby greatly affecting the cost. Compartmentalization is very difficult to determine. Compartmentalization is best analyzed by history matching production over many years.[Dake 2001] However, this approach is simply not practical in most new oil fields because higher cost markets require huge capital expenditures prior to first oil. Well testing is also useful when identifying compartments; however, the large cost of such activities, especially offshore, precludes widespread use. Consequently, compartments must be identified without benefit of well testing. Compartments and DFA - There are a number of reasons why compartments are difficult to locate [Mullins 2008]. First, no formation evaluation measurements exist that can image (thin) sealing barriers at the reservoir length and scale. Methods incorporating DFA have proved the existence of compartments that are invisible to petrophysical well logging [Mullins 2008, Mullins 2005]. Second, the standard industry approach to compartment identification is to presume pressure communication