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Abstract

The Karachaganak field is one of the largest accumulation of gas-condensate in the world, in production since 1985. Located in the northern Pricaspian Basin (Kazakhstan) the field is a Permo-Carboniferous isolated carbonate platform with a hydrocarbon column that resides within different environments of deposition. The distribution of reservoir properties has been largely debated because of both the depositional heterogeneity and the diagenetic overprint. These uncertainties were assessed by analyzing and integrating the vast amount of geological and production data to build a predictive history matched reservoir model. Seismic facies analysis, with support from outcrop analogues and integrated with field core and log data, reveals, within stratigraphic intervals, C"depositional regionsC" (DRs) that ranges from platform interior bedded deposits to aggrading/prograding mounds, clinoforms, slopes and basin sediments. These DRs were first seismically mapped and then petrophysically characterized using geologic and dynamic data. In a geologically meaningful manner that makes use of DRs, a sequence of better and better models was built and critical petrophysical issues (such as enhanced/matrix permeability, sealing barriers and dolomitization) were in parallel addressed. A reference model has been so defined and a history match of remarkable quality has been achieved for this complex heterogeneous reservoir. The uncertainty was investigated in a pragmatic manner using HM as benchmark. The reservoir uncertainty decreases closer and closer to the well, hence various models were built by updating DR properties up to a certain distance from the production wells. Using the distance and the magnitude of the perturbations as control parameter and the degree of history match as selection criterion, we could identify two cases. These scenarios represent possible alternative C"end membersC" consistent with the geological data, still endorsed by a high quality history match and capable to give a significant spread in the production forecast.

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/content/papers/10.3997/2214-4609-pdb.293.F041
2012-06-04
2019-12-15
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http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609-pdb.293.F041
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