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.