This paper provides a critical review of the integrated reservoir management process implemented to maximize ultimate recovery by maintaining an optimum reservoir pressure distribution in a low transmissibility sector of a giant carbonate reservoir. The peripheral water injection is the main driving mechanism in this reservoir due to the excellent areal transmissibility from the flanks towards the center of the reservoir. However, the study area is limited and characterized by a various degree of low transmissibility due to the degradation in reservoir quality and the presence of a tar mat at the flanks. The main challenge is to provide an adequate pressure support far away from the peripheral injection line and to sustain the required production capacity from the study area. Conventional peripheral water-flooding is insufficient to meet the ever increasing production capacity without an optimized injection set-up consisting of up-dip and down-dip peripheral injectors.The study demonstrates that cohesive understanding of the flow mechanism, which entails integration of various sources of information, is crucial to achieve successful pressure maintenance and voidage replacement schemes. Consequently, detailed characterization of the tar region was constructed through multiple realizations covering the entire spectrum of uncertainties and impacts on reservoir performance. The injection efficiency over various production scenarios was also carried out using finite-difference and streamline tracing to capture the interaction between producers and injectors. In addition, a coupled subsurface-surface integrated modeling was utilized to identify bottle-necks and evaluate development options.Production performance and acquired reservoir surveillance data vindicated the implemented practices. Optimum reservoir pressure distribution was observed over the entire study area. Conventional and advanced open-hole log results from strategically placed evaluation wells and time lapses of saturation logs from key monitoring wells over a 5 years period indicated favorable areal and vertical sweep efficiency.

A single well tracer test (SWTT) is a method to investigate the residual oil saturation near the wellbore. It presents an important tool to evaluate enhanced oil recovery (EOR) processes. For EOR evaluation, two SWTTs (one before and another after EOR application) can be used to estimate the reduction in S or due to the application of an EOR process. The change in S or is a measure of the incremental oil recovery of the applied EOR technology. In this work, we use University of Texas Chemical Flooding Simulator to guide the design of SWTTs that will be later run to evaluate chemical flooding potential. First, we perform thorough sensitivity simulations using an idealistic homogeneous model. Second, we perform simulations using a realistic model, which was generated based on the selected evaluation well (Well-X). In the sensitivity runs, we investigate the effects of various parameters such as partitioning coefficients, reaction rates, injection rates, injection volumes, and shut-in times. Based on the results, we provide recommendations for designing the SWTTs. Furthermore, simulations using the Well-X model suggest an incremental oil recovery factor of 14.7 % OOIP due to surfactant-polymer flooding. This is consistent with lab data and provides assurance to multi-well field applications. More importantly, those simulation results support the utility of SWTTs in evaluating chemical flooding potential. Based on the results, we expect to observe distinct back-production peaks, clear separation between the reactive and product tracers, and measurable variation in separation due to chemical EOR application that can be categorically analyzed.

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This paper presents an application of probabilistic, ensemble-based computer-Assisted History Matching (AHM) with uncertainty to Integrated Reservoir Model (IRM) of a Middle Eastern reservoir. The paper outlines the most important characteristics of the AHM workflows for rigorous quantification of model uncertainty, optimization of history matching parameters and execution of large-scale reservoir simulations using Massive Parallel Processing technology. The AHM approach integrates probabilistic Bayesian inference using Ensemble Smoother with Multiple Data Assimilation (ES-MDA), which simultaneously assimilates the data and generates maximum a-posteriori updates of reservoir model parameters in a variance-minimizing update scheme. Variability and sensitivity analyses are conducted to identify the most dominant reservoir parameters and a large number of geo-cellular model realizations is generated to rigorously capture the uncertainty ranges. The AHM workflow was applied to a synthetic Dual-Porosity Dual-Permeability (DPDP) oil reservoir model with approximately (~) 34 million grid-cells. The simulation model span ~50 years of production with flank water injection. The optimization objective was to minimize the joint misfit of watercut, oil-rate and static well pressure in ~50 producing wells and improve well-level history match. An enhancement of AHM workflow is proposed to improve the simulation model connectivity as well as the accuracy of the history match by implementing the streamline-based approach to update fracture network through drainage volume analysis of injector-producer pairs. While the computational performance of the used ES-MDA algorithm was found very robust and fairly independent of the geological and engineering complexity of studied simulation cases, the overall complexity of IRMs can raise memory-allocation, computation and information technology (IT) communication challenges. The paper discusses these challenges and proposes measures to alleviate them for successful deployment of AHM workflows to large-scale models.

TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractA redevelopment strategy for a hydrocarbon producing reservoir in a complex geological environment is presented in this paper. With the application of the IOR technology, the hydrocarbons, which seemed to be hidden in unreachable parts of the reservoir, became economically extractable, increasing the value of the field. The thin oil column and the large gas cap are trapped in a low permeability turbidite type sandstone reservoir. The thickness of layers separated by interbedded claymarles is less than 10 meters of each. In the first 15-year production period 12% oil recovery could be reached from the reservoir having 10 mD average permeability. At starting of the production the depletion mechanism was gas cap expansion combined with weak water drive (1975)(1976)(1977)(1978)(1979)(1980)(1981)(1982)(1983)(1984)(1985). The initially flowing wells started to produce with artificial gas lift in 1980. Water injection was necessary to maintain the reservoir pressure so this technology was launched in 1985. In the early 90's the reservoir had very poor economics because of the low productivity and injectivity of vertical wells. The forecasted production rates had been keeping to the economic limit. 1993 was a mileage in the production history because the first horizontal well was drilled and completed in the reservoir. By the end of 1999 the number of horizontal oil wells was increased up to 20 inducted by the excellent production results. During this production period, the continuous reservoir monitoring reflected the problems of different phases of exploitation and what kinds of solution alternatives were induced by the integrated interpretation of the increasing information obtained from production history. This paper answers how the production potential of the reservoir could be doubled in the last seven years and how the forecasted ultimate oil recovery increased to over 40%. Redevelopment of this producing object was reached by the IOR technique. Infilling of the producing well pattern and acceleration of exploitation was the key in this mature reservoir. With 3.6 USD/bbl investments an additional 5.2 million equivalent barrel reserve became proved.