Dissertations / Theses on the topic 'Reservoir geology'

The Spraberry Formation is a Leonardian age submarine fan deposit restricted to the Midland Basin. The formation consists of very fine-grained sandstone, medium to coarse grain size siltstones, organic shales and carbonate mudstones. These rocks show variability in sedimentary structures and bedding types varied from thinly laminated to convolute laminations. Bioturbations were present in some samples and soft sediment deformation, such as water escape features, sediment loading and flame structures.

The Spraberry Formation is a naturally fractured reservoir with low porosity and low matrix permeability. Porosity measured varied from 2% in rocks with poor reservoir quality such as the argillaceous siltstone and mudstone while good reservoir rocks had an average porosity of 9%. Seven lithofacies were identified based on sedimentary structures, grain size and rock fabrics. Petrographic analysis showed four porosity types: (1) intragraular porosity; (2) dissolution porosity; (3) fracture porosity and (4) intergranular porosity. Fractured porosity was only observed in the argillaceous siltstone lithofacies.

The prominent diagenetic influences on the Spraberry Formation are: quartz cementation, quartz overgrowth, illtization of smectite, feldspar dissolution, clay precipitation, carbonate cementation, formation of framboidal pyrite and fracture formation. These diagenetic features were observed using scanning electron microscope (SEM) and in thin sections. Generally, petrophysical properties, such as porosity and permeability, vary gradually from reservoir rocks to non-reservoir rock. Observed trends where: 1) increasing organic and argillaceous content with decreasing porosity and 2) increasing carbonate sediments and calcite cements with decreasing porosity. Mineralogical analysis from FTIR showed an abundance of quartz and calcite, while illite is the prominent clay mineral observed in all samples.

Compositional analysis of reservoir rock is a vital aspect of oil exploration and production activities. In a broad sense, knowing the mineral composition of a reservoir can help with characterization and interpretation of depositional environments. On a smaller scale, identifying mineralogy helps calibrate well logs, identify formations, design drilling and completion programs, and screen for intervals with potential problem minerals, such as swelling clays. The petroleum industry utilizes two main methods to find compositional mineralogy, x-ray diffraction (XRD) and thin section analysis. Both methods are time consuming, expensive, and destructive. An alternative method for compositional analysis that includes quantitative mineralogy is a valuable prospect, especially if it had the potential to characterize the total organic content (TOC).

The remote sensing community has been using infrared spectroscopy to analyze mineralogy for years. Within the last ten years, the advancement of infrared spectrometers and processing programs have allowed infrared spectra to be taken and analyzed faster and easier than before. The objective of this study is to apply techniques used in remote sensing for quantitatively finding mineralogy to the petroleum industry. While developing a new methodology to compositionally analyze reservoir rock, a database of infrared spectra of relevant minerals has been compiled. This database was used to unmix spectra using a constrained linear least-squares algorithm that is used in the remote sensing community. A core has been scanned using a hand-held infrared spectrometer. Results of the best method show RMS error from mineral abundance to be under five percent.

The presence of shale in a sandstone reservoir can negatively affect the producibility of that reservoir. It is hence important to quantify not only the volume of shale but also the distribution types. The shale distribution types are described as laminar shale, dispersed shale, and structural shale. The shale distribution types can exist in any number of combinations in a reservoir. However, most previous works have considered only the single-type distribution models (laminar, dispersed, and structural shales) and the two-type laminar-dispersed and laminar-structural models. A previous thesis expanded on previous works to include the dispersed-structural and three-type shale distribution system, expanding the total porosity versus total volume of shale crossplot technique, and devised the ratio method for further analysis. This research provides an additional methodology to quantify the shale distribution types using the density porosity versus neutron-density volume of shale crossplots. Applying the ratio method in terms of the gamma-ray volume of shale and neutron-density volume of shale showed that considering a third component in the volume of shale distribution led to an increase in the volume of dispersed shale. Both the laminar-dispersed and laminar-structural models provide the most optimistic scenarios in the reservoir where the volume of dispersed shale is calculated at its lowest potential value and, hence, the effective sandstone porosity is highest. The ratio method allows for the calculation of a range of scenarios starting from the most optimistic to the most pessimistic. Using the VshND tool as an additional method in a case study in this work revealed that the VshND calculated the volume of shale at higher values than the VshGR, thus providing a more conservative analysis in this case.

The objective of this study is threefold: 1) Build a dual-porosity, geological reservoir model of Niobrara formation in the Wishbone Section of the DJ Basin. 2) Use the geologic static model to construct a compositional model to assess performance of Well 1N in the Wishbone Section. 3) Compare the modeling results of this study with the result from an eleven-well modeling study (Ning, 2017) of the same formation which included the same well. The geologic model is based on discrete fracture network (DFN) model (Grechishnikova 2017) from an outcrop study of Niobrara formation.

This study is part of a broader program sponsored by Anadarko and conducted by the Reservoir Characterization Project (RCP) at Colorado School of Mines. The study area is the Wishbone Section (one square mile area), which has eleven horizontal producing wells with initial production dating back to September 2013. The project also includes a nine-component time-lapse seismic. The Wishbone section is a low-permeability faulted reservoir containing liquid-rich light hydrocarbons in the Niobrara chalk and Codell sandstone.

The geologic framework was built by Grechishnikova (2017) using seismic, microseismic, petrophysical suite, core and outcrop. I used Grechishnikova’s geologic framework and available petrophysical and core data to construct a 3D reservoir model. The 3D geologic model was used in the hydraulic fracture modeling software, GOHFER, to create a hydraulic fracture interpretation for the reservoir simulator and compared to the interpretation built by Alfataierge (2017). The reservoir numerical simulator incorporated PVT from a well within the section to create the compositional dual-porosity model in CMG with seven lumped components instead of the thirty-two individual components. History matching was completed for the numerical simulation, and rate transient analysis between field and actual production are compared; the results were similar. The history matching parameters are further compared to the input parameters, and Ning’s (2017) history matching parameters.

The study evaluated how fracture porosity and rock compaction impacts production. The fracture porosity is a major contributor to well production and the gas oil ratio. The fracture porosity is a major sink for gathering the matrix flow contribution. The compaction numerical simulations show oil production increases with compaction because of the increased compaction drive. As rock compaction increases, permeability and porosity decreases. How the numerical model software, CMG, builds the hydraulic fracture, artificially increases the original oil-in-place and decreases the recovery factor. Furthermore, grid structure impacts run-time and accuracy to the model. Finally, outcrop adds value to the subsurface model with careful qualitative sedimentology and structural extrapolations to the subsurface by providing understanding between the wellbore and seismic data scales.

The Short Time Fourier transform and the S-transform are among the most used methods of spectral decomposition to localize spectra in time and frequency. The S-transform utilizes a frequency-dependent Gaussian analysis window that is normalized for energy conservation purposes. The STFT, on the other hand, has a selected fixed time window that does not depend on frequency. In previous literature, it has been demonstrated that the S-transform distorts the Fourier spectra, shifting frequency peaks, and could result in misleading frequency attributes. Therefore, one way of making the S-transform more appropriate for quantitative seismic signal analysis is to ignore the conservation of energy over time requirement. This suggests a hybrid approach between the Short Time Fourier transform and the S-transform for seismic interpretation purposes. In this work, we introduce the Multi-Scale Boxcar transform that has temporal resolution comparable to the S-transform while giving correct Fourier peak frequencies. The Multi-Scale Boxcar transform includes a special analysis window that focusses the analysis on the highest amplitude portion of the Gaussian window, giving a more accurate time-frequency representation of the spectra in comparison with the S-transform. Post-stack seismic data with a strong well logs control was used to demonstrate the differences of the Multi-Scale Boxcar transform and the S-transform. The analysis area in this work is the Pennsylvanian and Lower Permian Horseshoe Atoll Carbonate play in the Midland Basin, a sub-basin in the larger Permian Basin. The Multi-Scale Boxcar transform spectral decomposition method improved the seismic interpretation of the study area, showing better temporal resolution for resolving the layered reservoirs? heterogeneity. The time and depth scale values on the figures are shifted according to the sponsor request, but the relative scale is correct.

This thesis describes the advantages of investigating gas shales reservoir description on a nanoscale by using petrographic analysis and core plug petrophysics to characterize the Barnett, Marcellus and Mancos shale plays. The results from this analysis now indicate their effects on the reservoir quality. Helium porosity measurements at confining pressure were carried out on core plugs from this shale plays. SEM (Scanning Electron Microscopy) imaging was done on freshly fractured gold-coated surfaces to indicate pore structure and grain sizes. Electron Dispersive X-ray Spectroscopy was done on freshly fractured carbon-coated surfaces to tell the mineralogy. Extra-thin sections were made to view pore spaces, natural fractures and grain distribution.

The results of this study show that confining pressure helium porosity values to be 9.6%, 5.3% and 1.7% in decreasing order for the samples from the Barnett, Mancos and Marcellus shale respectively. EDS X-ray spectroscopy indicates that the Barnett and Mancos have a high concentration of quartz (silica-content); while the Mancos and Marcellus contain calcite. Thin section analysis reveals obvious fractures in the Barnett, while Mancos and Marcellus have micro-fractures.

Based on porosity, petrographic analysis and mineralogy measurements on the all the samples, the Barnett shale seem to exhibit the best reservoir quality.

The Pine Prairie Field is situated on a salt dome in northern Evangeline Parish, located in south-central Louisiana. Pine Prairie contains the only known Cook Mountain Formation hydrocarbon reservoir in Louisiana. Operators have targeted and produced hydrocarbons from the Cook Mountain reservoir in eight wells at the Pine Prairie Field. The source and origin of the Cook Mountain’s reservoir properties are unknown. The objective of this study is to determine the origin of the Cook Mountain Formation’s reservoir properties by identifying the processes associated with the formation of a Cook Mountain Reservoir. There are two carbonate outcrops at the surface expression of the Pine Prairie Dome. Samples were taken and thin sections made to determine the relationship, if any, to the Cook Mountain Formation. Thin section analysis of the carbonate outcrop was used to gain a better understanding of the depositional setting present at Pine Prairie Field. Well log, seismic, and production data were integrated to determine that, in all instances, commercial Cook Mountain production is associated with fault zones. The passage of acidic, diagenetic fluids through Cook Mountain fault zones generated areas of vuggy porosity proximal to Cook Mountain faulting. Further, fluctuations in short-term pressure gradients associated with salt diapirism resulted in the vertical migration of hydrocarbons via fault zones. In the Pine Prairie Field, fault seal breakdown occurs in Sparta and Wilcox Reservoirs, subsequently charging the Cook Mountain fault zone. Early hydrocarbon charge from the underlying Wilcox and Sparta Reservoirs prevented additional diagenesis, preserving secondary porosity in areas of Cook Mountain faulting.