Identifying oil-saturated versus water-saturated sands in shallow, unconsolidated, viscous-oil-bearing terrigenous-clastic reservoirs of Kuwait field is challenging. Field appraisal was based upon seismic, core and wireline-log data from 19 wells. Static and dynamic models incorporating all subsurface data were built to estimate oil-in-place and forecast production. Estimating and modeling fluid saturations in reservoir zones was accomplished by integrating core, dielectric-resistivity, Nuclear Magnetic Resonance (NMR) and Wireline Formation Tester (WFT) data. Wells were drilled along a northwest/southeast-trend, thus geologic and reservoir-property variability in east and west parts of the field are uncertain. Stratigraphy and lithologic properties in these Miocene-age fluvial to shallow-marine strata impart a complex 3–D fluid distribution in the field. Repeated shoreline progradations and retrogradations deposited a stratigraphic succession defined by five facies-associations (i.e., shoal, tidal flat, tidal channel, lagoon, sabkha). Five lithofacies (i.e., shale, shaly sandstone, sandstone, carbonate-cemented sandstone, evaporite) were identified from core, elemental spectroscopy logs, and X-ray diffraction (XRD) data. Facies associations and lithofacies models were built using a combination of multiple-point statistics and sequential-indicator simulation. Lithofacies distribution in the static model was constrained by the facies-association distribution; reservoir-property distribution (e.g., porosity, permeability) was conditioned by lithofacies. Discrete reservoir zones were defined to separate oil-saturated versus water-saturated sands. The volume and position of oil-bearing sands are controlled by the defined zones and permeability distribution. The oil-filling process in these viscous oil-bearing reservoirs is typically controlled by the pore throat distribution with the migrating oil taking the path of least resistance. Due to the presence of stratigraphic-flow baffles, fluid contacts vary from sand-to-sand vertically and laterally. Log data, core descriptions, ultraviolet photographs, WFT and pressure volume temperature (PVT) data guided the interpretation of lowest known oil and highest known water levels, thus reducing fluid saturation uncertainty in the field.
To evaluate uncertainty in property distribution and reservoir connectivity, resource size, and development plans for Verkhnechonskoye, a large Precambrian oil field, three geologic models were built employing:Sequential Indicator Simulation (SIS) and Sequential Gaussian Simulation (SGS);Object Modeling; andSeismic-Attribute Modeling. Reservoir models were based on seismic and wireline-log, core, and well-test data from over 100 wells. The reservoir consists of sandstone, mudstone, and rare conglomerate deposited on a broad alluvial plain fringing an igneous and metamorphic continental island. Coarse-grained sediments were deposited in channels that prograded and aggraded the alluvial plain that terminated downdip into a lacustrine or epicontinental sea. In places, lagoons and poorly developed beaches fringed the alluvial plain. Relative base level created upward-coarsening and upward-fining successions that onlap the basement. Shale beds create flow barriers while, porosity and permeability are primarily controlled by evaporate, quartz, and calcium carbonate cements. Buildup and interference tests were designed using estimated average reservoir properties. Test results discriminated among the three geologic models for use in field-development planning. Partial field-simulation models were upscaled from each geologic model and used to match the buildup and interference tests. The SIS model surpassed the Object and Seismic models in matching well performance. This better match of well performance from the SIS model occurred because sandstones are better connected and exhibit more homogeneous rock properties as compared to the Object or Seismic models. It was concluded that the SIS method of facies and property distribution is preferred for future modeling in the field. Introduction The Precambrian Verkhnechonskoye field is located approximately 600 kilometers north of Irkutsk, Eastern Siberia, in the Russian Federation (Fig. 1). To assist in evaluating uncertainty in property distribution and reservoir connectivity, resource size, and development planning, 3-D geocellular models of terrigeneous-clastic reservoirs in the Verkhnechonskoye field, were built using data from wireline logs, 2D and 3D seismic, cores and porosity/permeability analyses, and well tests. While an extensive exploration and appraisal program had established the existence of a significant hydrocarbon accumulation, the distribution of reservoir properties and reservoir connectivity were poorly understood. Both complex reservoir characteristics and uncertainties in existing data sets contributed to the lack of understanding of reservoir properties. Three geocellular models were constructed: one based on statistical distribution of wireline-log data (SIS model); the second, an object model using relationships derived from core descriptions (Object model); and a third based on seismic attributes (Seismic model). Specifically, the models constitute three geologic descriptions of the reservoir to test:the uncertainty in reservoir oil-in-place estimates;reservoir connectivity; andfield-development plans. Volumetric variation was shown to be small whereas, reservoir connectivity and property distribution varied significantly depending upon the modeling approach employed. Stratigraphic and sedimentologic interpretations relied heavily on cores from six wells. Wireline logs (100+ wells; Fig. 1) calibrated to cores provided lithology, porosity, permeability, and water saturation values distributed in the models. Interval property maps, structure maps, fault planes, and seismic facies were generated from 2D and 3D seismic data.
The Verkhnechonskoye field was discovered and appraised during the late 1970s and early 1980s. One hundred legacy wells and three modern wells have been reevaluated and results used to construct a static model that matched test results and was used to forecast field potential. The Verkhnechonskoye field is currently operated by TNK-BP. Cores in the three modern wells were studied to determine lithology, depositional facies, and mineralogy. Results were applied to crossplots of sonic and neutron log data. These crossplots showed six different lithofacies: basement, weathered-basement, high permeability sand, low permeability sand, salt/anhydrite-cemented sand, and carbonate. Sand was subdivided into relatively high and relatively low permeability sands using the laterolog and microlaterolog, based on the observation that sand with microlaterolog values less than 10 ohm-m were observed to be highly productive on test. To calculate porosity, the neutron, sonic, and core porosity were compared. Preliminary porosity was calculated using a field-wide solution from a combined crossplot of sonic log values and core data. Well by well analysis indicated that the sonic logs often underestimated porosity and that neutron logs tended to match core porosity better. Petrographic analysis confirmed that widespread secondary porosity was not detected by sonic logs. Single-well porosity solutions based on neutron logs were used together with sonic porosity calculations to finalize porosity estimates. For permeability, high and low trends were calculated for sands using the microlaterolog to define high permeability and low permeability sands. A relatively high permeability to porosity relationship was applied to sands with microlalaterolog values less than 10 ohm-m and a relatively low permeability to porosity relationship was applied to sand with microlaterlog values greather than 10 ohm-m.. A significant number of core permeability measurements were available and these points were honored after depth-shifting. Finally, log derived permeability was modified to match average permeability derived from well test results. Identification of multiple lithologies and calibration of porosity and permeability to core measurements and well test results signficantly reduced uncertainty in calculated results. Introduction Western petrophysicists tasked with evaluating Soviet era (legacy) wells in the Eastern Siberian Basin face a problem significantly different from workers in Western Siberia. There Western analysts can adapt Russian logs to customary methods of calculating shale volume, porosity, and water saturation then apply cutoffs to identify reservoir rock and pay. Statistical methods have been developed to convert Russian logs into Western equivalents (Carlston and Cluff, 2006), with an emphasis on generating a pseudo-density log, key to most Western petrophysical approaches. This approach is possible because Western Siberia is not, from a petrophysical standpoint, dissimilar to the moderate porosity shaley-sand setting seen and studied all over the world. The Eastern Siberian Basin, in contrast, offers an unusual and challenging combination of geology, drilling practices, and technology. To get the best possible results for each well, a unique approach has been developed to integrate all available data into a comprehensive answer.
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