This study shows how the use of modern geological investigative techniques can reopen old, “drained” hydrocarbon fields. Specifically, it looks at the White Castle Field in South Louisiana. This field has pay sections ranging from late Oligocene to late Miocene. The late Oligocene package is underexplored and understudied and contains 3 primary reservoirs (Cib Haz (CH), MW, and MR). This study established the depositional history of these reservoirs. During most of the late Oligocene, the White Castle Salt Dome was located in a minibasin on the continental slope. The CH and MW deposited in this minibasin. The CH is an amalgamation of slumped shelfal limestones, sandstones, and shales deposited during a lowstand systems tract (LST). The MW comprises a shelf-edge delta that is part of a LST. The MR is an incised valley fill located in the continental shelf that was deposited during LST after the minibasin was filled.

In 2007, the Barnett Shale in the Fort Worth basin of Texas produced 1.1 trillion cubic feet (Tcf) gas and ranked second in U.S gas production. Despite its importance, controls on Barnett Shale gas well performance are poorly understood. Regional and vertical variations of reservoir properties and their effects on well performances have not been assessed. Therefore, we conducted a study of Barnett Shale stratigraphy, petrophysics, and production, and we integrated these results to clarify the controls on well performance. Barnett Shale ranges from 50 to 1,100 ft thick; we divided the formation into 4 reservoir units that are significant to engineering decisions. All but Reservoir Unit 1 (the lower reservoir unit) are commonly perforated in gas wells. Reservoir Unit 1 appears to be clay-rich shale and ranges from 10 to 80 ft thick. Reservoir Unit 2 is laminated, siliceous mudstone and marly carbonate zone, 20 to 300 ft thick. Reservoir Unit 3 is composed of multiple, stacked, thin (~15-30 ft thick), upward coarsening sequences of brittle carbonate and siliceous units interbedded with ductile shales; thickness ranges from 0 to 500 ft. Reservoir Unit 4, the upper Barnett Shale is composed dominantly of shale interbedded with upward coarsening, laterally persistent, brittle/ductile sequences ranging from 0 to 100 ft thick. Gas production rates vary directly with Barnett Shale thermal maturity and structural setting. For the following five production regions that encompass most of the producing wells, Peak Monthly gas production from horizontal wells decreases as follows: Tier 1 (median production 60 MMcf) to Core Area to Parker County to Tier 2 West to Oil Zone-Montague County (median production 10 MMcf). The Peak Monthly oil production from horizontal wells is in the inverse order of gas production; median Peak Monthly oil production is 3,000 bbl in the Oil Zone-Montague County and zero in Tier 1. Generally, horizontal wells produce approximately twice as much oil and gas as vertical wells.This research clarifies regional variations of reservoir and geologic properties of the Barnett Shale. Result of these studies should assist operators with optimization of development strategies and gas recovery from the Barnett Shale.

In 2007, the Barnett Shale in the Fort Worth basin of Texas produced 1.1 trillion cubic feet (Tcf) gas and ranked second in U.S gas production. Despite its importance, controls on Barnett Shale gas well performance are poorly understood. Regional and vertical variations of reservoir properties and their effects on well performances have not been assessed. Therefore, we conducted a study of Barnett Shale stratigraphy, petrophysics, and production, and we integrated these results to clarify the controls on well performance. Barnett Shale ranges from 50 to 1,100 ft thick; we divided the formation into 4 reservoir units that are significant to engineering decisions. All but Reservoir Unit 1 (the lower reservoir unit) are commonly perforated in gas wells. Reservoir Unit 1 appears to be clay-rich shale and ranges from 10 to 80 ft thick. Reservoir Unit 2 is laminated, siliceous mudstone and marly carbonate zone, 20 to 300 ft thick. Reservoir Unit 3 is composed of multiple, stacked, thin (~15-30 ft thick), upward coarsening sequences of brittle carbonate and siliceous units interbedded with ductile shales; thickness ranges from 0 to 500 ft. Reservoir Unit 4, the upper Barnett Shale is composed dominantly of shale interbedded with upward coarsening, laterally persistent, brittle/ductile sequences ranging from 0 to 100 ft thick. Gas production rates vary directly with Barnett Shale thermal maturity and structural setting. For the following five production regions that encompass most of the producing wells, Peak Monthly gas production from horizontal wells decreases as follows: Tier 1 (median production 60 MMcf) to Core Area to Parker County to Tier 2 West to Oil Zone-Montague County (median production 10 MMcf). The Peak Monthly oil production from horizontal wells is in the inverse order of gas production; median Peak Monthly oil production is 3,000 bbl in the Oil Zone-Montague County and zero in Tier 1. Generally, horizontal wells produce approximately twice as much oil and gas as vertical wells.This research clarifies regional variations of reservoir and geologic properties of the Barnett Shale. Result of these studies should assist operators with optimization of development strategies and gas recovery from the Barnett Shale.

Increasing hydrocarbon reserves by finding new resources in frontier areas and improving recovery in the mature fields, to meet the high energy demands, is very challenging for the oil industry. Reservoir characterization and heterogeneity studies play an important role in better understanding reservoir performance to meet this industry goal. This study was conducted on the Boonsville Bend Conglomerate reservoir system located in the Fort Worth Basin in central-north Texas. The primary reservoir is characterized as highly heterogeneous conglomeratic sandstone. To find more potential and optimize the field exploitation, it’s critical to better understand the reservoir connectivity and heterogeneity. The goal of this multidisciplinary study was to quantify the permeability heterogeneity of the target reservoir by integrating core, well log and 3D seismic data. A set of permeability coefficients, variation coefficient, dart coefficient, and contrast coefficient, was defined in this study to quantitatively identify the reservoir heterogeneity levels, which can be used to characterize the intra-bed and inter-bed heterogeneity. Post-stack seismic inversion was conducted to produce the key attribute, acoustic impedance, for the calibration of log properties with seismic. The inverted acoustic impedance was then used to derive the porosity volume in Emerge (the module from Hampson Russell) by means of single and multiple attributes transforms and neural network. Establishment of the correlation between permeability and porosity is critical for the permeability conversion, which was achieved by using the porosity and permeability pairs measured from four cores. Permeability volume was then converted by applying this correlation. Finally, the three heterogeneity coefficients were applied to the permeability volume to quantitatively identify the target reservoir heterogeneity. It proves that the target interval is highly heterogeneous both vertically and laterally. The heterogeneity distribution was obtained, which can help optimize the field exploitation or infill drilling designs.

All the oil and gas wells producing in the Arikaree Creek Field, Colorado targeted the Spergen Formation along similar structures within a wrench fault system; however, the wells have vastly different production values. This thesis develops a predictive model for high production in the field while also accounting for a failed waterflood event that was initiated in 2016. Petrophysical analysis of thirteen wells show that high producing wells share common characteristics of pay zone location, lithology, porosity and permeability with one another and that the Spergen Formation is not homogenous. Highly productive wells have pay zones in the lower part of the formation in sections that are dolomitized, and have anonymously high water saturation. This is likely related to the paragenesis of the formation that dolomitized the lower parts of the formation, increasing porosity and permeability, but leaving the pay zones with the high water saturation values. This heterogeneity likely accounts for the failed waterflood. Results show that the important petrophysical components for highly productive wells are the location of the payzone within the reservoir, porosity, permeability and water saturation. Additionally, homogeneity is crucial for successful waterflooding, which was not present.

A novel data analysis approach that is automatic, self-learning and self-explained, and which provides accurate and reliable results is reported. The data analysis tool is capable of performing multivariate non-parametric regression analysis, as well as quantitative inferential analysis using predictive learning. Statistical approaches such as multiple regression or discriminant analysis are usually used to perform this kind of analysis. However, they lack universal capabilities and their success in any particular application is directly affected by the problem complexity.The approach employs the use of Artificial Neural Networks (ANNs) and Fuzzy Logic to perform the data analysis. The features of these two techniques are the means by which the developed data analysis approach has the ability to perform self-learning as well as allowing user interaction in the learning process. Further, they offer a means by which rules may be generated to assist human understanding of the learned analysis model, and so enable an analyst to include external knowledge.Two problems in the resource industry have been used to illustrate the proposed method, as these applications contain non-linearity in the data that is unknown and difficult to derive. They are well log data analysis in petroleum exploration and hydrocyclone data analysis in mineral processing. This research also explores how this proposed data analysis approach could enhance the analysis process for problems of this type.

The SACROC unit is an isolated carbonate platform style of reservoir that typifies a peak icehouse system. Icehouse carbonate platforms are one of the least well understood and documented carbonate reservoir styles due to the reservoir heterogeneities they embody. The current study is an attempt to recognize carbonate rock types defined based on rock fabrics by integrating log and core based petrophysical analysis in high-frequency cycle (HFC) scale sequence stratigraphic framework and to improve our ability to understand static and dynamic petrophysical properties of these reservoir rock types, and there by, improve our understanding of heterogeneity in the middle early to late early Canyon (Canyon 2) high frequency sequence (HFS) in the Northern Platform of the SACROC Unit. Based on core descriptions, four different sub-tidal depositional facies were defined in the Canyon 2 HFS. Identified depositional facies were grouped into three different reservoir rock types in respect to their rock fabrics in order for the HFC scale petrophysical reservoir rock type characteristic analysis. Composed of succession of the identified reservoir rocks, twenty different HFCs were determined within the HFC scale sequence stratigraphic framework. The overall trend in the HFCs demonstrate systematic coarsening upward cycles with high reservoir quality at the cycle tops and low reservoir quality at the cycle bottoms. It was observed in terms of systems tracts described within the cycle scale frame work that the overall stacking pattern for high stand systems tracts (HST) and transgressive systems tracts (TST) is aggradational. And, the reservoir rocks representing the HST are more porous and permeable than those of TST. In addition to that, it was detected that the diagenetic overprint on the HST reservoir rocks is more than that of the TST. According to the overall petrophysical observations, the grain-dominated packstone deposited during HST was interpreted as the best reservoir rock. Upon well log analysis on the identified reservoir rocks, some specific log responses were attributed to the identified reservoir rocks as their characteristic log signatures. / text

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Our understanding of fine-grained sediment regarding the processes in which they are transported and deposited is rapidly evolving. However, developing a depositional model and characterizing the vertical variability within mud-dominated deposits has seldom been done. A 103m Upper Mancos Shale core retrieved from the San Juan Basin, New Mexico was analysed with detailed thin-bedded facies analysis to observe vertical variability in lithology, sedimentary structures, bioturbation intensity, and depositional processes. Lithological variation suggests there are 3 full sequences, 9 system tracts, and 92 parasequences. Facies observed revealed multiple facies successions indicating depositional processes including ignitive turbidite, storms (tempestite), wave enhanced sediment gravity flows (WESGFs), tidal, biogenic reworking, fluid mud, suspension settling, and general bedload transport. Relationships between lithology, bioturbation intensity, sedimentary structures and depositional processes were observed to be interrelated in that energetic processes (i.e., storms, ignitive turbidite) were associated with coarser deposits and low bioturbation intensity; whereas lower energy processes (i.e., biogenic reworking, suspension settling, WESGFs) were associated with finer deposits and relatively higher bioturbation intensities. Furthermore, lithological variability integrated with depositional models indicated temporal changes in environment of deposition across shelf. / Thesis / Master of Science (MSc)