This thesis introduces a rock typing method for application in shale gas reservoirs using conventional well logs and core data. Shale gas reservoirs are known to be highly heterogeneous and often require new or modified petrophysical techniques for accurate reservoir evaluation. In the past, petrophysical description of shale gas reservoirs with well logs has been focused to quantifying rock composition and organic-matter concentration. These solutions often require many assumptions and ad-hoc correlations where the interpretation becomes a core matching exercise. Scale effects on measurements are typically neglected in core matching. Rock typing in shale gas provides an alternative description by segmenting the reservoir into petrophysically-similar groups with k-means cluster analysis which can then be used for ranking and detailed analysis of depth zones favorable for production. A synthetic example illustrates the rock typing method for an idealized sequence of beds penetrated by a vertical well. Results and analysis from the synthetic example show that rock types from inverted log properties correctly identify the most organic-rich model types better than rock types detected from well logs in thin beds. Also, estimated kerogen concentration is shown to be most reliable in an under-determined problem. Field cases in the Barnett and Haynesville shale gas plays show the importance of core data for supplementing well logs and identifying correlations for desirable reservoir properties (kerogen/TOC concentration, gas saturation, and porosity). Qualitative rock classes are formed and verified using inverted estimates of kerogen concentration as a rock-quality metric. Inverted log properties identify 40% more of a high-kerogen rock type over well-log based rock types in the Barnett formation. A case in the Haynesville formation suggests the possibility of identifying depositional environments as a result of rock attributes that produce distinct groupings from k-means cluster analysis with well logs. Core data and inversion results indicate homogeneity in the Haynesville formation case. However, the distributions of rock types show a 50% occurrence between two rock types over 90 ft vertical-extent of reservoir. Rock types suggest vertical distributions that exhibit similar rock attributes with characteristic properties (porosity, organic concentration and maturity, and gas saturation). This method does not directly quantify reservoir parameters and would not serve the purpose of quantifying gas-in-place. Rock typing in shale gas with conventional well logs forms qualitative rock classes which can be used to calculate net-to-gross, validate conventional interpretation methods, perform well-to-well correlations, and establish facies distributions for integrated reservoir modeling in hydrocarbon-bearing shale. / text

Horizontal drilling and hydraulic stimulation make hydrocarbon production from organic-rich shales economically viable. Identification of suitable zones to drill a horizontal well and to initiate or contain hydraulic fractures requires detection and quantification of many factors, including elastic mechanical properties. Elastic behavior of rocks is affected by rock composition and fabric, pore pressure, confining stress, and other factors. Rock fabric refers to the arrangement of the rock’s solid and fluid constituents. The objective of this thesis is to quantify rock fabric properties of hydrocarbon-bearing shales affecting elastic properties, including load-bearing matrix, anisotropic cracks, and shape of rock components. Once rock fabric is validated with sonic logs, results can be used to identify suitable zones to drill a horizontal well, initiate hydraulic stimulation, and contain fracture propagation. We develop a method to estimate elastic properties based on rock composition. The differential effective medium (DEM) theory is invoked to model rock elastic properties with a load-bearing component in which remaining minerals and pores are added as spheres or ellipsoids. The method can be combined with the self-consistent approximation (SCA) to construct a load-bearing matrix made of two solid phases. Anisotropic inclusions are added via Hudson’s model. Subsequently, Gassmann’s theory is invoked to saturate the rock with fluids and determine low-frequency elastic properties for comparison to sonic logs. Rock fabric properties remain constant in a vertically homogeneous formation. In vertically heterogeneous strata, the depth interval of interest is divided into rock types, based on rock solid composition, and each rock type is associated with a specific fabric. Quantification of rock fabric properties is a non-unique process, and one should take into account as much petrophysical and geological information as possible to ensure physically viable results. Our simulation and interpretation method is implemented in two wells in both the Haynesville and Barnett shales. Averages of relative errors between estimated velocities and sonic logs are less than 4% in the four wells. Simulations in the Haynesville shale are isotropic, and therefore indicate that rock fabric may not be the main cause of mechanical anisotropy in cases where such behavior is inferred from field data. Rock fabric properties are constant with depth in both wells. Consequently, identification of suitable zones to drill a horizontal well or to contain fracture propagation is not based on rock fabric; it is deduced from Young’s modulus. Simulated Poisson’s ratio is shown to be more sensitive to errors in velocities than Young’s modulus and is therefore not used in the interpretation. Favorable depth intervals for gas production exhibit sizeable volumes of gas and organic content. In the Barnett shale, the two wells exhibit different rock fabrics. Such a behavior indicates that the formation is laterally heterogeneous. Rock physics models should therefore be extrapolated from one well to another with caution. Simulations assume anisotropic elastic behavior and suggest the presence of compliant horizontal pores in one case. Natural vertical fractures are observed on electric image logs in the remaining case and are modeled with Hudson’s theory. This behavior suggests that rock fabric causes mechanical anisotropy in the formation. Heterogeneity of the Barnett shale rock fabric is inferred from the necessary use of rock typing to adequately reproduce sonic logs in both wells. Intervals with large porosity and high gas saturation identify suitable zones to perform hydraulic stimulation. Among such zones, rock types that exhibit stiff load-bearing matrices (comprising mostly calcite, for example) indicate suitable depths to drill horizontal wells or to contain hydraulic fractures. Intervals with dense layering of different rock types are unsuitable for fracture propagation and should be avoided during hydraulic-fracturing operations. / text

The purpose of this investigation is to determine the effectiveness of projective well log analysis based upon data collected from Plummer Field located in Greene County, Indiana. Projective well log analysis consists of analyzing spontaneous potential (SP) logs from existing oil and gas wells in order to determine SP gradients that may be applied to locate other undiscovered hydrocarbon accumulations. Projective well log analysis was developed in 1963 by S.J. Pirson, however, the specific parameters employed in the Plummer Field investigation were developed in 1988 by Dr. R.H. Fluegeman in order to apply to the geologic conditions in southwestern Indiana.The results of this investigation indicate that SP gradients can be interpreted to determine hydrocarbon production potential in Plummer Field with a 62% to 73% certainty. Given the petroleum industry exploration success rate of 3% to 20%, it is believed that the SP gradients established in Plummer Field can be used to identify economical hydrocarbon accumulations in areas of similar geology such as other portions of the Illinois Basin and the Michigan Basin. / Department of Geology

Thesis (M.S.)--West Virginia University, 2004. / Title from document title page. Document formatted into pages; contains ix, 123 p. : ill. (some col.), maps (some col.). Includes abstract. Includes bibliographical references (p. 108-109).

Thesis (Ph. D.)--University of Texas at Austin, 1999. / Vita. Includes bibliographical references (leaves 169-173). Available also in a digital version from Dissertation Abstracts.

Thesis (M.S.)--West Virginia University, 2000. / Title from document title page. Document formatted into pages; contains ix, 111 p. : ill. (some col.), map. Includes abstract. Includes bibliographical references (p. 110-111).

Thesis (M.S.)--West Virginia University, 2006. / Title from document title page. Document formatted into pages; contains vi, 84 p. : ill. (some col.), maps (some col.). Includes abstract. Includes bibliographical references (p. 79-82).

Thesis (M.S.)--West Virginia University, 2006. / Title from document title page. Document formatted into pages; contains ix, 148 p. : ill. (some col.), maps (some col.). Includes abstract. Includes bibliographical references (p. 145-148).

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In this paper, we design and develop a new software tool that helps automatic lithofacies segmentation from geological data. Lithofacies is a crucial problem in reservoir characterization, and our study intends to prove that soft computing techniques like Wavelet transform modulus maxima lines (WTMM) and Detrended fluctuation analysis (DFA) approaches allow a geological lithology segmentation from differed well logging. On one hand, WTMM proves to be useful for delimitation of each layer. We based on its sensitivity on the presence of more than one layer, On the other hand, DFA is used to enhance the estimation if the roughness coefficient of each lithology. We use them jointly to segment the lithofacies of boreholes located in the Algerian Sahara. Obtained results are encouraging to publish this method, because the principal benefit is economic.