Modeling and simulation of non-Darcy or turbulent flow are well documented in the literature and available in commercial reservoir simulators (E300, Intersect) only for gas wells rather than oil wells. There is a need to model non-Darcy or turbulent flow in reservoir simulation for oil wells in the carbonate reservoirs with highly connected and densely distributed fractures and karst. This paper proposes a new non-Darcy or turbulent flow modeling and simulation method for oil wells. Unlike the industry's existing methods for non-Darcy or turbulent flow that focus on the non-Darcy coefficient only, this paper presents a new method that models the ratio between non-Darcy and Darcy flows such that a unified model for a field or a region can be created, which significantly simplifies the non-Darcy or turbulent flow modeling process for multiple wells, especially for future wells. The ratio-based method is simple and comprehensive. It can be easily calibrated with MRT (multiple-rate test) data and implemented into in-house or commercial reservoir simulators using a simulator supported scripting language, e.g., Python etc. Kashagan is the world's largest oil reservoir discovered in the last 30 years that contains highly connected and densely distributed fractures and karst in its rim. The oil production rate for a well in the rim can be higher than several tens KSTB/D if it is not constrained by the facility. The current MRT data in all tested wells clearly show non-Darcy flow phenomenon and confirm that modeling non-Darcy flow is necessary to the field. Kashagan had experienced difficulties to match BHP (bottom hole pressure) and large errors in the blind test due to the OPEC's production curtailment and high-rate tests. Build-up pressure curves were miss-matched and HM (history match) of the crossflows (10 KSTB/D with less than 10 psi) in the bottomhole of a PLT (production logging tool) well during shut-in was challenging. Since modeling non-Darcy flow for oil wells in the commercial simulators, e.g., E300 and Intersect, is unavailable, the simulation team in NCOC has created a new method for the needs of non-Darcy modeling and simulation. The applications of the new method have resulted in the excellent results and solved the issues of history matching BHP, high/low-rate tests, build-up pressure trends, and bottomhole crossflows.

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During early production of Kashagan Field, the surveillance program is critical for understanding connectivity within the reservoir. Pressure transient analysis (PTA) results in the rim facies of the Kashagan carbonate platform show well bore proximity to high permeability features. By integrating the PTA results in a fine-scale geologic model, the presence and magnitude of geologic features, including faults, karst bodies, and open fractures, can be evaluated as an explanation of pressure results. Good quality pressure transient data can be obtained from down-hole gauges during periods of production down-time. The character of the pressure-response can provide information to interpret reservoir properties such as permeability-thickness (kh) and the effect of geologic features in the vicinity of the well. In the Kashagan rim area, geologic features include seismically-visible karst features, seismically-interpreted faults, and open fractures that can be identified from wireline logs. Because fine-scale details of the flow properties could not be differentiated in the full field simulation model, a fine-scale sector model of the rim area was constructed using Petrel ™ software. By integrating the surveillance and geologic data, the subsurface team can make several key observations. Rim wells with cavernous karst features contain kh values up to two orders of magnitude higher than stratigraphically-equivalent platform interior wells. Wells that produce from open fractures in the rim are commonly adjacent to seismically visible faults and karst geobodies, and the distance from the well to the seismically-visible geologic feature is similar to the distance estimated from the PTA results. At present, the kh interpretations from PTA are the only direct estimates of permeability for the large geologic features in the Kashagan rim. In a fine-scale 3D sector model, the permeability of the geologic objects, including faults, karst geobodies, and open fractures is statistically distributed using the PTA results. The fine-scale sector model demonstrates the value of geologic and surveillance data integration in order to understand PTA results. By establishing a relationship between the distance to geologic objects and PTA-based permeability estimates, a powerful predictive model can be developed to better represent the flow along the rim and guide the placement of future drill-wells.