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Brown-field Experimental Design (ED) was successfully applied to a super-giant oilfield to generate probabilistic (P10, P50, and P90) models to define the range of field performance and to mitigate the non-uniqueness in reservoir simulation. A recent trend in reservoir simulation has been to apply probabilistic modeling, such as, brown-field ED to develop multiple (P10, P50, and P90) models. Unfortunately, these probabilistic models are also non-unique because multiple input combinations can be used to generate the probabilistic responses observed during ED.The non-uniqueness of the probabilistic models may impact their usefulness in certain circumstances. For example, if these models are used to develop short-term signposts for long-term reservoir behavior, then the models may be influenced by the selection of reservoir data (e.g., a P10 model with one combination of input may have a different short-term "signature" than an alternate P10 model despite giving comparable P10 recovery). Also, the degree of success of a downside-mitigation (or upside-capture) strategy, and its ranking with other such strategies may be influenced by the input chosen to develop the models.For the super-giant Tengiz oilfield, brown-field ED was applied to a conventional history match with the primary objective of creating probabilistic models. Additionally, we developed tools to design multiple deterministic models with specific physical interpretations. With these deterministic models we can identify the signatures for specific reservoir phenomenon, such as, minimum/maximum OOIP, minimum/maximum compartmentalization, minimum/maximum reservoir energy, etc. All models built with these tools yield acceptable visual and quantitative history matches.In this paper we discuss how brown-field ED was used to post-process a conventional history match. We present a case study for the use of brown-field ED methods and illustrate the proposed approach to mitigate the non-unique nature of reservoir simulation. While the impact non-uniqueness can be mitigated, we also recognized that it can never be completely eliminated. 2 SPE 159341 Yuzhnaya Guryev Arch Tengiz Korolev 50 km Isolated Carbonate Platforms

Brown-field experimental design techniques were applied to the Tengiz super-giant carbonate reservoir. This brown-field study combined experimental design, reservoir simulation, and available historical pressure and production data to develop proxies to predict the history match quality and oil recovery of equally probable reservoir realizations. The authors used experimental design techniques similar to those documented in Landa et. al.1 and King et al.2; however, the effort documented in this paper incorporated a much larger brown-field component and highly non-linear response surfaces required many more runs (control points) to generate reliable proxies. The initial simulations runs included a folded Plackett-Burman design with a centerpoint run and sensitivity analysis runs which varied the input parameters that were known to affect the history match. The results from these runs were analyzed using regression analysis and ANOVA techniques to determine the most significant factors and to understand the complexity of the response surfaces. With this knowledge, D-optimal runs were designed and run to better understand the effect of the interaction of the significant factors on the response surfaces. Additional sensitivity analysis runs were also made to further define the effect of the two most important factors on the response surfaces: OOIP and reservoir transmissibility. With a total of 107 unique runs, the authors were able to develop five proxies to assess history match quality and one proxy to predict oil recovery. With the developed proxies, the authors used Monte Carlo techniques to generate equally probable reservoir/development scenarios. By using the history match quality proxies the authors were able to filter out combinations of subsurface parameters that caused unacceptable deterioration in the history match. The use of the five unique filters allowed the authors to significantly reduce uncertainty relative to the unfiltered simulation results. The results from this work were supported by material balance studies. Introduction The Tengiz Oilfield is a giant, fractured, carbonate field of Devonian age located in the Republic of Kazakhstan on the shoreline of the Caspian Sea (Figure 1). The field was discovered by the Oil Ministry of the former Soviet Union in 1979; put onto production in 1991; and has been operated by Tengizchevroil (a joint venture company comprised of Chevron, ExxonMobil, KazMunaiGas, and LukArco B.V.) since 1993. The Tengiz Field consists of a single reservoir which is subdivided into five sequences (from oldest to youngest: Devonian, Early Visean, Late Visean, Serpukhovian, and Bashkiriran (Figure 2). The details of these sequences have been discussed previously in the literature.3,4 To date, the majority of production from the field has come from the Serpukhovian-Bashkirian sequence. The Tengiz crude oil is a sour (approximately 13% H2S), 47° API, undersaturated oil with a bubble-point pressure of 3,660 psia. The initial reservoir pressure was approximately 11,950 psia at 14,765 ft TVD ss. The field was produced under primary production until 2007 when a pilot miscible gas injection project was initiated. Despite the injection of miscible gas, the principal production mechanism in the field will remain solution gas drive.

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The Korolev Field is located in western Kazakhstan where a waterflood pilot is planned in a sour naturally fractured carbonate reservoir. The completion design of the water supply and injection wells plays a key role in the economic oil recovery in a waterflood. An improper design can result in high cost, poor sweep efficiency, and low injectivity. This paper provides guidelines and technical studies on the completion designs for the Korolev Waterflood Pilot. The process for selecting the completion design consists of field data acquisition, analysis, and a completion alternatives assessment. Injection data are acquired from a short-term injection test in the targeted reservoir. Core and fluid samples are acquired from the water source aquifer. The data are analyzed to determine the completion design parameters and objectives for the wells. Finally, the completion alternatives are assessed by a cross functional team through a method which determines an optimum design based on the completion objectives. A summary of the key conclusions for the Korolev Waterflood Pilot completion designs are:Short-term injection test confirmed viable injection rates, operating pressures and the need for conformance control liner to improve the injection profile.Sand control is required in the lower completion of water supply wells to control solids production. The fines migration study provided key design information which allowed optimization of the water treatment facility design.The water supply wells preferred completion design is an open hole gravel pack with wire wrap screen.The water injection wells preferred completion design is a conformance control liner with swell packers and sliding sleeves. This assessment is an effective approach for unlocking the hydrocarbon potential in harsh wellbore conditions for a waterflood project. Cost discipline, simplification and cross-functional team work are the key elements which resulted project cost savings and partner alignment on the design and execution plan.