Gas shales are economically viable hydrocarbon prospects that have proven to be successful in North America. Unlike conventional hydrocarbon prospects, gas shales serve as the source, seal, and the reservoir rock. Generating commercial production from these unique lithofacies requires stimulation through extensive hydraulic fracturing. The absence of an accurate petrophysical model for these unconventional plays makes the prediction of economic productivity and fracturing success risky.This paper presents an integrated approach to petrophysical evaluation of shale gas reservoirs, specifically, the Barnett Shale from the Fort Worth basin is used as an example. The approach makes use of different formation evaluation data, including density, neutron, acoustic, nuclear magnetic resonance, and geochemical logging data. This combination of logging measurements is used to provide lithology, stratigraphy and mineralogy. It also differentiates source rock intervals, classifies depositional facies by their petrophysical and geomechanical properties, and quantifies total organic carbon. The analysis is also employed to locate optimal completion intervals, zones preferable for horizontal sections, and intervals of possible fracture propagation attenuation. Resistivity image analysis complements the approach with the identification of natural and drilling induced fractures. We compare results from three different wells to show the effectiveness of the method for shale gas characterization.The methodology presented provides a means to understand the geomechanical and petrophysical properties of the Barnett Shale. This knowledge can be used to design a selective completion strategy that has the potential to reduce fracturing expenses and optimize well productivity. Though developed specifically for the Barnett Shale, the underlying ideas are applicable to other thermogenic shale gas plays in North America.

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The successful recovery of hydrocarbons from gas shales requires a fundamental understanding of the reservoir's rock-matrix properties. Information about the variable lithologies, mineralogies, and kerogen content is vital to locate favorable intervals for gas production. Knowledge of the in-situ stresses and porosity of these intervals is essential for developing hydraulic fracturing strategies to recover the gas in place. Often these properties are established from the analysis of cores extracted from the wellbore, a time-consuming practice which causes costly delays in well completions and prolonged rig time. We demonstrate that these reservoir rock properties can be measured and predicted in-situ from the wellbore environment by a formation evaluation method that employs a combination of measurements made by downhole geochemical, acoustic, and nuclear magnetic resonance sondes. Using this combination of tool measurements we determine lithology, mineralogy, and kerogen content. The mineralogy, porosity, acoustic velocities, bulk density, pore pressure, and overburden stress are then used to compute the unconfined compressive strength, Poisson's ratio, and horizontal stress for each interval. These results can then be used to develop hydraulic fracture strategies. The effectiveness of this approach is shown through characterization of the rock properties of the Caney and the Woodford Shale from three different wells. The ability to quantify the kerogen content from these formations is emphasized as there is currently no other direct quantification of carbon from openhole wireline logging available. This approach for characterization of shale gas reservoirs is also further supported through comparisons of core data that display the mineralogy, chemistry, kerogen content, and geomechanical properties from the wellbore section. Introduction The Woodford and Caney formations comprise a successive series of fissile, carbonaceous, siliceous black shales that are unconventional, economic gas plays in the Arkoma Basin of eastern Oklahoma (Amsden, 1967; Cardot, 1989, Brinkerhoff, 2007, Schad, 2007). Producing commercial gas from these fine grained lithologies requires the stimulation of a large volume of rock using hydraulic fracture techniques. The projected azimuth, propagation, and containment of the induced fractures created using this method are sometimes difficult to predict. Fracture growth is impeded when stimulation stages do not successfully target siliceous lithofacies with lower fracture gradient. These can often induce extensive intersecting fractures or contain dormant mineralized fractures that upon reactivation may increase production. Instead, some stages are inadvertently applied to argillaceous zones that attenuate fracture development due to embedment. Other stages may be directed toward carbonate facies that have high breakdown pressures. Treatment pressures simply are unable to exceed the fracture gradient of the rock. Stimulations may also propagate along fault planes intersecting other formations within the basin leaving much of the reservoir rock unfractured (Vulgamore et al., 2007). Because of these problems, there can be uncertainty about whether there has been fracture containment within the zone of interest or whether optimal zones that promote gas recovery have indeed been fully accessed. For example, induced fractures into the Woodford can pose questions of whether these have been contained within the target area or have grown upward into the overlying Caney or downward into the underlying Hunton limestone. The differences in geochemical, petrophysical and geomechanical properties of the lithofacies found in both the Caney and Woodford can be used to improve hydraulic fracture strategies. Using a combination of logging tool measurements, we determine the kerogen content, porosity, mineralogy, and the principal stresses of the various lithofacies from the wellbore environment for three wells. Results will show how the integration of these into a petrophysical model provides reservoir characterization properties comparable to those gained from core analysis, which has the potential to save money and expedite well completions.

[1] An accurate description of water-or oil-bearing reservoirs strongly depends on a robust determination of their petrophysical parameters, e.g., porosity, permeability and fluid distribution. Downhole logging measurements are the primary means to formation evaluation; however, they do not directly provide the petrophysical properties of interest. To interpret well logging data, a range of empirical models are usually employed. These empirical relationships, however, lack scientific basis and usually represent generalizations of the observed trends. Since macroscopic rock properties vary depending on their microstructure, we suggest using a pore-scale approach to establish links between various petrophysical properties of sedimentary rocks. We outline a method for computing formation permeability using the proposed rock models. The method utilizes NMR (Nuclear Magnetic Resonance) logging data for the information about porosity and grain size. We also present an approach for prediction of acoustic velocities of model rocks. The proposed methodology is applied to the field data, and the corresponding interpretation results are included in this paper.Citation: Gladkikh, M., D. Jacobi, and F. Mendez (2007), Pore geometric modeling for petrophysical interpretation of downhole formation evaluation data, Water Resour. Res., 43, W12S08,

The assessment of reservoir productivity and subsurface hydrocarbon can be significantly enhanced through an understanding of formation mineralogy and organic carbon. Such information allows petrophysicists to resolve ambiguities in their predictions of reservoir hydrocarbon potential. While core samples are a prime source for exact formation mineralogy, excellent results can also be derived in a timely and cost-efficient manner from in-situ log chemistry measurements of the rock. A direct measurement of the formation's elemental concentrations is achieved using a gamma ray scintillation sensor in combination with a 14-MeV pulsed-neutron generator. The most important element measured is carbon, as it may provide a direct indication of reservoir hydrocarbons. This paper presents a method for determining the amount of organic carbon in subsurface formations using a pulsed-neutron mineralogy tool and a natural gamma ray spectroscopy tool. The natural, inelastic, and capture gamma ray energy spectra from these instruments are used to extract the chemistry of the subsurface formation being investigated. The elemental concentrations measured include Al, C, Ca, Fe, Gd, K, Mg, S, Si, Th, Ti, and U. Carbon is very difficult to measure without the inelastic spectrum generated from a pulsed-neutron source. An interpretation process, based upon the geochemistry of petroleum-bearing formations, is employed to derive the lithology and mineralogy which leads to the interpretation of the carbon measurement. The oil saturation can be computed in conventional reservoirs, assuming that the amount of carbon in excess of that required for the inorganic matrix mineralogy is part of the pore fluid as hydrocarbon. The direct carbon measurement is also important in laminated shaly sands or in low-salinity reservoirs, where oil saturation determination from indirect measurements, such as resistivity, is not compatible with the environment. In other formations the carbon can be determined to be a component of the rock matrix as kerogen or coal, both of which are uniquely identified with this logging system. Kerogen becomes extremely important in the evaluation of shale gas formations. Field examples are presented to illustrate the effectiveness of the carbon measurement. Introduction Subsurface organic carbon, i.e., carbon that does not belong to any of the carbonate minerals, indicates the presence of oil, natural gas, coal, or kerogen. Although the amount of carbon is one of the most important quantities in formation evaluation, openhole tools often provide only indirect measurements of hydrocarbons. Traditional electrical tools, for example, measure oil saturation indirectly based upon a comparison of the resistivity of saline and non-saline formation fluids. This approach works best when the salinity of the formation water is high to moderate; if connate water salinity is low, resistivity methods cannot differentiate water from hydrocarbon.

A new openhole logging service, RockViewSM, has been developed which provides lithological and quantitative mineralogical information for accurate formation evaluation. The assessment begins with elemental formation weights and follows with an interpretation of lithology and mineralogy. Lithologies are divided into general categories including sand, shale, coal, carbonates, and evaporites. Potentially identifiable minerals are quartz, potassium-feldspar, albite, calcite, dolomite, siderite, anhydrite, illite/smectite, kaolinite, glauconite, chlorite, pyrite, and others. The logging system utilizes an electronic pulsed source to send high energy neutrons into the surrounding formation1–8. These neutrons quickly lose energy as a result of scattering, after which they are absorbed by the various atoms within the ambient environment. The scattered as well as the absorbed neutrons cause the atoms of the various elements to emit gamma rays with characteristic energies. These are measured with a scintillation detector, resulting in both inelastic and capture gamma ray energy spectra. A matrix inversion spectral fit algorithm is used to analyze these spectra in order to separate the total response into its individual elemental components. The prominent measured elements associated with subsurface rock formations include calcium, silicon, magnesium, carbon, sulfur, aluminum, and iron. Potassium, thorium, and uranium are measured separately with a natural gamma ray spectroscopy instrument9–11. The tool response is characterized for each individual element by placing it into formations of known chemical composition. Interpretation of the data begins with an assessment of the elemental formation weights, which then leads to a determination of lithology and mineralogy. Each step in the process is guided by the examination of ternary plots containing selected elements. Magnesium is an extremely important part of the interpretation process since it distinguishes dolomite from calcite and helps to identify various types of clay. Data from field examples is presented in order to illustrate the effectiveness of this technology. Introduction Traditional formation evaluation using log data involved interpretation of measurements that included natural gamma ray, neutron porosity, density, and resistivity. Over the past decade, there has been an increase in the number of petrophysicists who desire additional information, including mineralogy-based logs. Such data helps resolve ambiguities in the traditional methods and opens up the possibility for new deductions to optimize hydrocarbon production. If one is concerned about calcite or anhydrite cement in a sand matrix, for example, such suspicions can be resolved through a measurement of the amounts of Ca and S. Knowledge of the formation matrix components can also be used to provide a more accurate porosity through an enhanced interpretation of the neutron and density data. In general, the interpretation of any measurement can be enhanced when the formation matrix is understood. A deductive approach to mineralogy is described herein, which begins by identifying the general lithology associated with each tool measurement as follows:Elements ? General Lithology ? Specific Lithology ? Mineralogy

Spectral gamma ray tools provide insights into the mineral composition of formations and such data can be used to distinguish important features of the formation around the wellbore. However, it is a challenge in cased-hole cases to anticipate the attenuation effects of casing within various conditions of density and thickness in an efficient manner. In this work, an innovative reduced- order Monte Carlo modelling technique is presented for cased-hole environment spectrum analysis and, specifically, to numerically determine the attenuation effects of gamma ray transmission through different materials. The presented computational method is developed accounting for different casing and cement thicknesses, and sensor positions within the borehole. The reduced order model construction could be considered one level up from the regular Monte Carlo modelling procedure as it reduces the dimensionality induced by various parameters and therefore proves an extremely useful tool handling large-scale problems that are very common in complicated downhole environment. The adjusted source distributions are then utilized to generate and validate spectra to be applied for difference logging scenarios. Two exemplary field cases are presented: 1. An open-hole logged well; 2. The same set-up well but with steel casing. The reduced modelling techniques are applied to the both cases and the possible impacts of different variable. e.g. borehole size, mud weight and cement thickness on the sensor-obtained spectra are discussed. Future work will involve a series of case studies .e.g. the sensitivity assessment of formation impurities and an extension of the Monte Carlo computed elemental standards to a great variety of nuclear downhole sensor designs.

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