Unconventional shale reservoir evaluation and development are extremely challenging. One of the most dominating aspects is permeability, which is measured in the nano-darcy range. Although these wells are stimulated to enhance production, the presence or absence of natural fractures can have a large impact on the production results. In addition, the fracture variation across a reservoir can be substantial, leading to large production variations, even in adjacent wells. Gaining insight about the natural fracture system, both intersecting and around the borehole, is crucial and can often help determine the economic success of a well and/or reservoir. The standard means of fracture evaluation, such as borehole imaging, Stoneley permeability analysis, and azimuthal shear-wave anisotropy evaluation from cross-dipole, provide valuable information when evaluating fractures. These standard methods, however, can only investigate a limited area around the borehole—imaging looks at the borehole wall and the other borehole acoustic methods rely on refracted and guided modes that respond to an area as large as 2 to 4 ft out into the formation. The flexural wave from the dipole is one of the guided modes that generally reads the deepest and is used in the standard cross-dipole analysis. In addition to flexural mode, the dipole source creates shear body waves that radiate away from the borehole and into the formation. When these shear waves impinge on a fracture their energy reflects back to the borehole, enabling the facture to be imaged. The reflection strength is a function of the shear-wave polarization and the nature of the fracture, with the strongest response occurring from the shear waves intersecting a fluid/gas-filled fracture and polarizing in the fracture's strike direction. Another important aspect is that these shear waves have azimuthal sensitivity, providing a means to determine the fracture direction. These features enable the evaluation of fractures over a much larger area around the well, often in excess of 60 ft from the borehole, and even detecting major fractures that do not intersect the well. We will look at the application of this deep shear-wave imaging technology in several unconventional reservoirs across North America. Our review includes conventional methods and the deep shear-wave imaging analysis, showing its value in gaining important insight about the natural fracture system around the borehole, especially non-intersecting fractures. In addition, we will look at its application in mapping geologic structures in horizontal wells, demonstrating the ability to detect sub-seismic faults.
This paper compares rock physics trends in the Vp-vs.-Vs crossplot and the Vp/Vs-vs.-compressional slowness crossplot. Trend uncertainties are presented with laboratory data from the Bakken, Bazhenov, Monterey, and Niobrara shales; departures from expected trends attributed to kerogen, hydrocarbon, anisotropy, and well deviation are discussed. Anisotropy models, such as ANNIE (Schoenberg et al.1996), are presented for computing Thomsen parameters and stiffness coefficients. Castagna mudrock line (Castagna et al. 1993) derived from in-situ sonic and seismic measurements provided an average linear relationship between compressional and shear-wave velocities. Brie (1995) extended previous work to include predicting gas saturation from a Vp/Vs-vs.-compressional slowness crossplot. Projecting the Castagna mudrock line onto a shear-vs.-compressional slowness crossplot proved useful for interpreting sonic data. Classical-rock physics equations were used to model compressional and shear velocities as a function of well deviation. Laboratory anisotropy models allowed for characterizing the effects of dispersion, anisotropy, and well deviation. Anisotropic-rock physics models for the Bakken, Bazhenov, Monterey, and Niobrara organic shales are presented and compared in terms of the Thomsen parameters, ε, γ, and δ, and stiffness coefficients, Cij. These models are first transposed to trend curves in Vp-vs.-Vs, Vp/Vs-vs.-compressional slowness, and shear-vs.-compressional slowness crossplots and then compared to the Castagna mudrock trend curve. The anisotropy models are then applied to characterize the effect of well deviation on these trend curves. Results are also presented for well log data from the Eagle Ford, Haynesville, and Bakken formations in the context of the discussed crossplots and then compared with the expected trend curves. The Eagle Ford data satisfies the carbonate Vp-vs.-Vs trend predicted in previous literature by Castagna et al. (1993), and the Haynesville data clearly satisfies the gas effect predicted by the Brie Vp/Vs-vs.-compressional slowness crossplot discussed. In theory, the models describing anisotropy with the Thomsen parameters or stiffness coefficients are equivalent. In practice, not all the parameters for either model can be measured from log data. Preferentially, anisotropic models should be derived by combining log data from multiple vertical, deviated, and horizontal wells for each shale reservoir.
A new geochemical logging tool has been designed and developed for the precise determination of formation chemistry, mineralogy, and lithology, as well as the identification of total organic carbon (TOC). The primary elements identified by the system include aluminum, calcium, carbon, chlorine, hydrogen, iron, magnesium, oxygen, potassium, silicon, sulfur, thorium, titanium, and uranium. These elements are utilized to identify the minerals present in both conventional and unconventional formations. Tool operation begins by emitting high energy 14 MeV neutrons into the formation from a pulsed neutron generator, and the resulting gamma rays are intercepted by a high resolution, state of the art, LaBr3(Ce) detector. In order to exclude background gamma rays and provide a clean capture spectrum, a boron coating has been placed on the housing. The 3.25-inch tool diameter makes the system easier to operate in small boreholes as well as in horizontal wells. The extensive set of detected elements is made possible by the PNG, where high speed electronics are incorporated to accrue both capture and inelastic energy spectra. A Levenberg-Marquardt matrix inversion algorithm is employed to separate the spectra into their fundamental elemental components. Characterization of the system has been achieved through numerous measurements in more than 30 formations from a newly constructed Rock Formation Laboratory in Fort Worth, Texas as well as at the Callisto Facility in the United Kingdom. A significant number of core samples were obtained from these formations and analyzed for elemental and mineralogical composition. Extensive use of MCNP modeling was exploited for the design and characterization of the system. The final lithological and mineralogical interpretation is guided by the elemental concentrations of the various elements, as well as the computation of intrinsic sigma. Magnesium is used to differentiate between calcite and dolomite in carbonate formations. Aluminum, iron, and potassium, in addition to silicon, provide the information required to distinguish the various clays in sand/shale formations. Sulfur is vital for the identification of both pyrite and anhydrite. Ternary plots are generated to aid in the final interpretation. To demonstrate the effectiveness of this work, log examples from the field are provided.
Permeability is one of the most important petrophysical parameters in formation evaluation and reservoir description. Unlike porosity and saturation, permeability can be a non-zero rank tensor. Most published log-based permeability models are only used to determine scalar or isotropic permeability. However, more and more oil/gas reservoirs have been found in anisotropic formations. In these geological environments, the permeability, resistivity, and some other petrophysical parameters are frequently anisotropic. From an industry-wide viewpoint, very few logging tools provide measurements that can be used as inputs for the calculation of log-based permeability anisotropy (horizontal and vertical permeability). Multicomponent induction (MCI) tools are examples that can measure resistivity anisotropy. This paper describes the algorithms and interpretation workflow that can be used to assess permeability anisotropy from an integrated interpretation of resistivity anisotropy and conventional log-derived permeability. As an extension of present permeability models in isotropic formations, a new permeability model in an anisotropic formation is obtained. Based on this anisotropic model, a new relationship between resistivity anisotropy and permeability anisotropy is determined in anisotropic formations. This relationship shows that the permeability anisotropy is a function of the resistivity anisotropy ratio and pore structure parameters. By comparison, the previously published results include only a few special cases in the new relationship. Assuming that the log-derived permeability data are available and are calibrated based on the effective permeability or one component of the permeability tensor, the remaining permeability components can be obtained from the relationship of resistivity and permeability anisotropy. In thinly laminated shale-sand formations, log-derived permeability and horizontal or vertical permeability cannot accurately represent true reservoir permeability because of the vertical-resolution limitation of logging tools. To overcome this limitation, the true reservoir permeability is evaluated from the calculated horizontal and vertical permeability based on a multimodal permeability tensor model. For practical applications in anisotropic reservoirs, an interpretation workflow is presented for permeability anisotropy evaluation with the joint interpretation of resistivity anisotropy and log-derived permeability from conventional/advanced sensor logs (e.g., resistivity, imaging, and sonic). The algorithms and workflow are validated by using the numerical simulation and field data. The new workflow has been used in the permeability anisotropy interpretation of synthetic data with and without random errors. After the synthetic data validation, the workflow is applied to field log interpretation. Both applications showed that this new addition of the permeability anisotropy should significantly assist in the accurate assessment of the reservoir, as well as in fracture detection and subsequent oil development and production.
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