Shale gas and other unconventional gas plays have become an important factor in the United States energy market and are often referred to as statistical plays due to their high heterogeneity. They present real engineering challenges for characterization and exploitation, and their productivity depends upon an inter-related set of reservoir, completion and production characteristics.The Devonian Ohio shale of eastern Kentucky is the State's most prolific gas producer. The gas shale underlies approximately two-thirds of the state, cropping out around the Bluegrass Region of central Kentucky and having a sub crop beneath the Mississippi Embayment in western Kentucky. This paper describes the reservoir modeling and history matching of a Devonian Gas Shale Play, eastern Kentucky, its potential for CO 2 enhanced gas recovery and storage.A geologic model of the shale has been compiled from mineralogical, petrographic, core, production, and wireline data. The COMET3 multi-phase, dual porosity simulator is being used to investigate CO 2 injection into the shale for enhanced gas recovery. To accomplish this, a subset of wells surrounding the potential injection site has been selected for further study. These eight wells cover approximately 5,300 acres of productive shale. The reservoir was subdivided into the Upper Ohio and Lower Huron members. To capture geological heterogeneity, gas production rates for these wells served as a proxy to characterize fracture permeability using geostatistical methods. Well production was history matched applying an automated process. Finally, several CO 2 injection scenarios spanning huff-n-puff to continuous injection were reviewed to evaluate the enhanced gas recovery potential and assess the CO 2 storage capacity of these shale reservoirs.
An integrated methodology combining clustering analysis techniques, geostatistical methods and evolutionary strategy technologies was developed and applied to an area in the SACROC Unit (Permian basin). Clustering methods were applied to well logs and core data with high vertical resolution for many wells to predict porosity, permeability and rock type. Geostatistics was applied to extend the characterization into the inter-well area. Evolutionary strategies were used to refine the characterization to match historical production performance. The complete approach was tested on an area within the SACROC Unit, acknowledged as a highly heterogeneous carbonate reservoir with complex production history. Three cored wells provided porosity and permeability measurements on a foot-by-foot basis. These measurements coupled with well logs were used to predict porosity, permeability and flow units. Twenty two wells in the study area having foot-by-foot profiles of porosity and permeability were considered sufficient to characterize porosity and permeability in three dimensions. Geostatistical methods were then used to build porosity and permeability models. As a validation of the characterization procedure, evolutionary strategy jointly coupled with a black oil reservoir model was used to history match production performance of a 0.5 mi2 area. The 65,340 grid-block model had over 50 years of production. Thirteen (13) input parameters were varied during the history match. Among them, a multiplying factor was applied to the permeability realization to account for upscaling effects, varying permeability values without modifying geological heterogeneities identified during the characterization process. No adjustment to porosity characterization was permitted. A very good history match of individual production was achieved for the center wells of the area, and a good match was also obtained for outer wells production and reservoir pressure where boundary effects existed. This validates the new integrated clustering/geostatistical/evolutionary-strategy approach in this highly heterogeneous carbonate reservoir. Introduction An integrated methodology combining clustering analysis techniques, geostatistical methods and evolutionary strategy technologies was developed and applied to a study area in the SACROC Unit (Permian basin). Initially, a two-step "soft-computing" procedure was developed capable of efficiently generating core-scale porosity and permeability profiles at well locations where no core data existed. The approach applies clustering methods based on maximum likelihood principles to well logs and core data for lithology interpretation, reservoir quality characterization, and prediction of "core" parameter profiles, with high vertical resolution for many wells. This procedure permites to populate any well location with core-scale estimates of porosity and permeability (P&P), and rock types facilitating direct application of geostatistical techniques to build 3D reservoir models. Geostatistical methods are then applied to the resulting dataset, and three-dimensional spatial models of variability for clusters, porosity, and permeability are utilized to generate reservoir representations of P&P for flow simulation purposes. Finally, a computer assisted history matching based on application of evolutionary strategy technologies was used to history match the production performance of a selected subregion in the SACROC Unit (Permian basin).
The Southeast Regional Carbon Sequestration Partnership (SECARB), led by the Southern States Energy Board (SSEB) represents 11 southeastern states: and east Texas. The SECARB Partnership region contains multiple regional-scale geologic storage opportunities, which offer sufficient capacity to sequester the region's major point source CO 2 emissions for decades. These include deep saline formations, depleted oil and gas fields, organic-rich shale formations, Tertiary-age coal deposits of the northern Gulf of Mexico Basin, and coal deposits of the central Appalachian and Black Warrior Basins.Depleted oil and gas fields can provide excellent early sites for sequestering CO 2 in known porous and permeable reservoirs overlain by proven seal formations (confining units). In addition, many oil fields within the SECARB region offer opportunities for integrated application of CO 2 enhanced oil recovery (EOR) and CO 2 sequestration, potentially helping to accelerate CO 2 storage efforts. Depleted oil and gas fields could provide 29.7 to 34.7 gigatonnes (Gt, billion metric tons) of storage with nearly 24 million barrels incremental oil (otherwise stranded oil) that may be recovered. Sixty percent of this capacity is expected from offshore fields.Storage potential in deep saline formations is vast, estimated conservatively to range from 2,281 to 9,123 Gt. Recent assessment of one regional saline formation, the Upper Cretaceous age Lower Tuscaloosa Group and equivalent Woodbine Formation, estimates storage capacity of 19.8 to 79.5 Gt. Saline formations require comprehensive geologic characterization of the reservoir properties of the storage formation and the seal characteristics and continuity of potential confining units. Coal and organic-rich shale have significant adsorptive capacity for CO 2 and offer potential CO 2 storage with enhanced coalbed methane and shale gas production. Low-rank Tertiary coal of the northern Gulf of Mexico basin offers 20 to 28 Gt of potential storage capacity with an additional 1 to 2 Gt from coal seams of the central Appalachian and Black Warrior basins. However, the reservoir potential of Gulf of Mexico coal seams is largely unproven, whereas the Appalachian and Black Warrior basins host major coalbed methane operations. The CO 2 storage capacity of the Barnett Shale in the Fort Worth Basin is estimated to be 19 to 27 Gt. Other shale formations include the Fayetteville Shale of the Arkoma Basin, estimated to have 14 to 20 Gt of capacity, and a range of shale formations that have yet to be assessed in the Black Warrior Basin and Appalachian thrust belt. These include the Conasauga Formation (Cambrian), Devonian shale formations, and the Floyd Shale (Mississippian).Field validation of CO 2 injection and storage is critical for confirming CO 2 storage estimates, and are the primary path forward to commercialization. Field tests validate the geologic characterization effort and reservoir models, specifically injectivity, capacity and containment, and advance the state-of-the-art in measurement, m...
Shale gas and other unconventional gas plays have become an important factor in the United States energy market, and are often referred to as statistical plays due to their high heterogeneity. They present real engineering challenges for characterization and exploitation, and their productivity depends upon an inter-related set of reservoir, completion and production characteristics. Shale gas plays are generally characterized by low geologic risk and a high commercial risk. Extensive and continuous deposits of tight, usually naturally-fractured shale provide the duality of a potentially-productive reservoir being the hydrocarbon source. Commercial production is a huge unknown in these plays, and reservoir modeling as well as production predictions involve considerable uncertainty. Because of the large number of unknowns, a merely deterministic approach is often incapable of capturing the complete impact of all interdependencies present in a shale gas resource play. Consequently, one must take into account multiple scenarios to find better exploitation plans. Tools are therefore needed to identify the most important geologic and engineering factors, and to quantify the range of variability in uncertain variables. Reservoir simulation coupled with stochastic methods, i.e., Monte Carlo and geostatistical procedures, have provided excellent means to predict production profiles with a wide variety of reservoir character and producing conditions. Defining and representing uncertainties with a quantitative understanding of their respective impacts on commercial achievability is crucial to subsequent decisions involving continued investment for commercial purposes. This paper describes a systematic process employed in the evaluation of a new prospect area (a shale gas play) with very limited available data. In order to properly model the problem with uncertainty, geological and engineering issues were framed within conventional Monte-Carlo procedures and geostatistical characterization algorithms to identify key production parameters so that relevant data can be collected. This process also allows for the investigation of how the combination of a nested natural fracture system, appropriate wellbore design and stimulation are necessary to drive productivity, and provide project results in terms of ranges of outcomes and associated probabilities. Consequently, managers can be in a better position to make informed decisions regarding the uncertainty of such projects. Introduction The high degree of heterogeneity, and therefore production uncertainty, present in shale gas plays makes them an ideal candidate for further analysis employing statistical methods. Defining and representing uncertainties with a quantitative understanding of their respective impacts on commercial achievability is crucial to subsequent decisions involving continued investment for commercial purposes.
Nitrogen (N 2 ) and carbon dioxide (CO 2 ) injection has been a subject of enhanced coal bed methane (ECBM) and carbon capture and storage (CCS) research during the past decade. N 2 and CO 2 injection produce substantially different recovery processes. Coal has a higher affinity for CO 2 as compared to methane (CH 4 ). Preferential adsorption of CO 2 , a larger molecule than methane, onto the coal surface results in a dramatic decrease in cleat permeability due to coal swelling. This ultimately induces a loss of injectivity creating a significant technical hurdle for CCS operations in coal. In contrast, N 2 increases cleat permeability because of its lower coal storage capacity relative to methane . As a result, injectivity increases during N 2 -ECBM. Theoretically, the injection of a mixture of CO 2 and N 2 will result in ECBM and CCS without a loss of injectivity. This study presents an investigation of that concept.To identify key geological and reservoir parameters driving ECBM and sequestration processes in deep unminable coal seams, a Monte Carlo probabilistic approach was implemented. Results from tornado plots confirmed the major role that coal rank (Langmuir isotherms) and pressure-dependent permeability data play in ECBM processes. As coal rank determines the maximum gas-in-place that could be stored per volume of coal, average fracture permeability, matrix and pore compressibility, and differential swelling factors are predominant in coal capacity to flow water and gas phases, impacting both incremental methane production as well as injectivity.Additionally, cleat permeability will vary greatly in response to injected gas composition during ECBM process. To better understand the consequences of these permeability changes by coal rank, a parametric study was designed. First results show that, for a specific coal rank, ECBM can drastically improve by increase N 2 content in the injected gas stream. However, methane incremental recovery due to high N 2 content will increase up to a maximum N 2 concentration, or threshold: besides this threshold, breakthrough occurs too rapidly to generate additional methane recovery. This N 2 threshold varies between coal ranks, as pressure dependant parameters also vary relative to the rank.Finally, 100%N 2 injection scenarios per coal rank highlight permeability behaviors easily explained in theory but which would probably need additional laboratory measurements to better understand their physical meaning while encountered during "real world" problems.
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