Sour Gas Injection project has been successfully implemented in Tengiz field, achieving long term pressure maintenance in the platform area by re-injecting gas with high H2S concentration and improving oil recovery. From the recent gas saturation campaign, sweep efficiency in injection pattern has varied from 10 to 70%, with the highest sweep, as well as most of gas breakthroughs observed in Bashkirian interval. This represents effective and uniform piston like miscible displacement across whole Bashkirian that enhances oil production. Similarly, surveillance monitoring shows that due to higher depletion rate in same Bashkirian, it experiences higher exposure to injectant fluid (sour gas) causing elevated GOR production at surface, whereas, lower intervals remain at near solution GOR with lower sweep efficiency. Such, anisotropy between the upper and lower intervals in terms of reservoir pressure and sweep efficiency creates an opportunity for the development of lower intervals by implementing conformance control technology. Injectant breakthrough and GOR elevation in SGI wells create additional challenges for TCO, due to limited gas handling capacity at the plant processing facilities. Hence, isolation of Bashkirian will not only stimulate lower intervals to produce, but also, reduce GOR concerns. First pilot workover to isolate Bashkirian in SGI used chemical polymers. Polymers were injected into the formation and provided strong isolation of the target interval. As a result, time-lapse gas saturation logs confirmed significant increase in vertical sweep efficiency across whole Unit-1 intervals, plus lower GOR production lasted for more than 6 years. Completion type variety in existing SGI wells, make application of chemical polymers challenging, therefore, conformance control completions were introduced as an alternative solution. Conformance control liner provides mechanical isolation between compartments for more effective staged acid stimulation treatments and enable potential isolation of unwanted fluids. This paper will introduce application of various conformance control techniques to alter production in SGI pattern by developing lower intervals and reducing elevated GOR. A gas shut-off campaign was initiated in Tengiz field after a decade of sour gas injection. Case studies will be presented to share challenges and results during planning and execution phases.

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Korolev field is a large Devonian-Carboniferous carbonate buildup with a flow system dominated by natural fractures. Currently TCO is looking into potential IOR opportunities at Korolev field, which might help to unlock additional resources beyond the scope of current development plans. Therefore, characterization and modeling of the fracture system is of fundamental importance for a new flow- simulation model to assess and predict IOR performance. The fracture modeling workflow closely integrates matrix and fracture modeling, which facilitates identification of important parameters for fracture distribution early in the modeling process. Fracture prediction is based on correlations with various geological parameters, such as stratigraphy, depositional facies, mechanical properties and geomorphological features, which provides a soft probability trend for distribution of fracture parameters. Fracture network characterization based on analysis of well log and core data only is very limited in scale. Pressure Transient Tests (PTT) and Pulse Tests provide important insights into characteristics of fracture network at the larger scale than the conventional wireline data allows. Therefore, it is important to incorporate dynamic dataset as a fracture characterization constraint during modelling of fracture distribution. Most of the wells at Korolev field have good quality pressure buildup and pulse test data. TCO developed a workflow to incorporate dynamic data into the fracture modeling process for the full- field dual porosity, dual permeability (DPDK) model. The first step in the workflow is to calibrate fracture density distribution to match well productivity indices (PI) observed in the field. The next step involves dynamic simulation of pressure buildup tests and their comparison to the actual measured data. The last step is to validate the geologic model with available pulse test data. Dynamic data integration required multiple iterations and loopbacks to fracture characterization and property distribution. Close collaboration between fracture experts, earth scientists and reservoir engineers along the whole process was essential for successful implementation of dynamic data into fracture characterization and modeling. Calibration with the available dynamic data led to better understanding of spatial distribution of fracture properties and provided important additional constraint for the fracture model construction. Improved fracture model at Korolev is the key factor for more reliable production forecasts and evaluation of future development opportunities.

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Tengizchevroil (TCO) is the biggest operator in Kazakhstan developing two world's deepest supergiant oilfields - Tengiz and, its satellite field, Korolev. With over 20 years of oil production at TCO, reservoir pressure has been declining and is approaching bubble point pressure. In order to arrest the declining pressure trend and extend oil production plateau, TCO is evaluating Improved Oil Recovery (IOR) opportunities, including potential Waterflood in Korolev field. Accurate Waterflood evaluation requires improved characterization of the main uncertainties impacting ultimate recovery under IOR processes. Therefore, we built next-generation Korolev reservoir model (SIM15K) which incorporates results of the latest characterization efforts based on the latest wide- azimuth 3D seismic survey. This work led to updated Korolev depositional model, which helps to understand the links between geological settings and fracture occurrence. In conjunction with the first implementation of Dynamic Data Integration workflow, this resulted into updated Low-Mid-High fracture models - one of the main factors controlling Waterflood performance in naturally-fractured reservoirs. This paper focuses on Brownfield Experimental Design (ED) of Korolev field, which is specifically designed to provide an estimate of IOR Incremental Recovery. We identified 23 main uncertainty parameters for each Low-Mid-High Fracture models. The Brownfield ED was run with two development scenarios: Primary Depletion and Waterflood to get probabilistic assessment of Incremental Waterflood Recovery. Overall 803 cases were required for each fracture model and development scenario to generate good quality proxies for cumulative recoveries and History-Match error. Those proxies were used to sample the entire space of uncertainties and define P10/50/90 targets. As a result of robust Brownfield ED, we selected P10/50/90 models to capture both range in Incremental Waterflood Recovery and Ultimate Recovery under Primary Depletion. The underlying uncertainty parameters for the final model selection were picked based on their relative impact on the objective functions. Currently, the new SIM15K model is being used for Korolev Waterflood evaluation and optimization, Reserves estimation, existing infrastructure optimization and future projects design.