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Collaborating Authors
Results
New Application of Old Data by Utilizing Long Duration Pressure Transient Tests and Permanent Downhole Gauges as High Value Assets for Improving Full Field Simulation Model with Additional Interference
Levchenko, Pavel (Tengizchevroil) | Iskakov, Elrad (Tengizchevroil) | Manakhayev, Ruslan (Tengizchevroil)
Abstract Accurate fracture characterization has a huge impact on production forecasts and evaluation of projects in Naturally Fractured Carbonate fields. Pulse/Interference Tests can give valuable information about fracture network by providing additional constraint for spatial fracture distribution between wells, which can be honored with application of geologically consistent trends (Levchenko et.al, 2017). However, operational execution of the Pulse/Interference tests is very challenging. Therefore, usually limited data are available from the planned surveillance jobs leaving large sections of the reservoir without information from Pulse/Interference tests, which could be used for calibration of the Fracture Model. Lack of Interference data can be resolved by examining already available measurements, which are generally used for other purposes. For example, the primary purpose of Pressure Transient Tests (PTTs) is obtaining kh and skin values, while Permanent Downhole Gauges (PDHG) are mostly utilized for recording reservoir pressure, which is used for conventional History Matching process. As it was found from this study, historical data from both PTTs and PDHGs could be a source of additional high value information of Interference tests occurring in the field, which nobody was aware of. Properly designed Pulse/Interference Tests are very difficult to execute in the field with high production deliverability requirements. However, examining historical data can reveal a lot of good quality Interference Tests, which were recorded and stored for decades, but not used for Fracture Model characterization. Additional information from Interference tests were applied to calibrate a full-field simulation model, significantly improving quality of the history match in comparison with previous models, and improved confidence in the production forecasts.
- Asia > Kazakhstan > Mangystau Oblast > Precaspian Basin > Tengiz Field > Tengiz Formation (0.99)
- Asia > Kazakhstan > Mangystau Oblast > Precaspian Basin > Tengiz Field > Korolev Formation (0.99)
- Asia > Kazakhstan > Mangystau Oblast > Precaspian Basin > Korolev Field (0.99)
Abstract 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.
- Geology > Geological Subdiscipline > Geomorphology (0.48)
- Geology > Geological Subdiscipline > Stratigraphy (0.34)
- Geophysics > Seismic Surveying (1.00)
- Geophysics > Borehole Geophysics (1.00)
- Asia > Kazakhstan > Mangystau Oblast > Precaspian Basin > Tengiz Field > Tengiz Formation (0.99)
- Asia > Kazakhstan > Mangystau Oblast > Precaspian Basin > Tengiz Field > Korolev Formation (0.99)
- Asia > Kazakhstan > Mangystau Oblast > Precaspian Basin > Korolev Field (0.99)
Abstract 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.
- Asia > Kazakhstan > Mangystau Oblast > Precaspian Basin > Tengiz Field > Tengiz Formation (0.99)
- Asia > Kazakhstan > Mangystau Oblast > Precaspian Basin > Tengiz Field > Korolev Formation (0.99)
- Asia > Kazakhstan > Mangystau Oblast > Precaspian Basin > Korolev Field (0.99)
- Africa > Angola > South Atlantic Ocean > Lower Congo Basin > Area B > Block 0 > Nemba Field (0.99)