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Abstract The Eagle Ford Shale hydrocarbon-fluid properties depend on the source rock maturity and, within the formation, occur in varying degrees of gas, gas condensate, and oil. Using conventional logs and pyrolysis data, several log-core regressions, such as delta log R, density, and uranium, can be derived to predict total organic carbon (TOC). The TOC can be used in conjunction with geochemical elemental measurements for a more accurate assessment of the formation kerogen and mineralogy, as well as hydrocarbon volumes. Nuclear magnetic resonance (NMR) porosity measures an apparent total porosity in the organic shale plays, measuring only the fluids present and excludes the kerogen. The complex refractive index method (CRIM) in conjunction with the mineralogy log data can be used to compute accurate dielectric porosities, which exclude both kerogen and hydrocarbon. Integrating the core TOC, predicted TOC, mineral analysis, NMR, and dielectric information, a final verification of the kerogen volume, hydrocarbon content, and mineral analysis can be assessed. This paper will describe the integration of conventional logs, a geochemical log, an NMR log, and dielectric to predict TOC, kerogen volume, and hydrocarbon volume, as well as, total porosity and mineralogy. The data is compared to the actual core data from three Eagle Ford wells, and it will be shown how the proposed approach will eliminate some coring operations. Finally, it will be shown how these interpretation results can be rolled up to make decisions on where to drill the lateral.
- Geology > Petroleum Play Type > Unconventional Play > Shale Play (1.00)
- Geology > Geological Subdiscipline > Geochemistry (1.00)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock > Shale (0.73)
- North America > United States > Texas > West Gulf Coast Tertiary Basin > Eagle Ford Shale Formation (0.99)
- North America > United States > Texas > Sabinas - Rio Grande Basin > Eagle Ford Shale Formation (0.99)
- North America > United States > Texas > Maverick Basin > Eagle Ford Shale Formation (0.99)
- (13 more...)
Abstract Accurate quantification of total organic carbon (TOC) is an important step in evaluating log data in organic-rich reservoirs. The literature describes many log-based approaches for predicting TOC that have been introduced over the years, including the use of uranium content or GR linear regression, bulk density, the DeltaLogR approach, neural network approach, and a response equation-based method using sonic, density, and resistivity logs. All of the approaches require core-to-log calibration for validation. Each of these techniques involves assumptions for them to be valid, and, in a given instance, it is possible some techniques will not produce reliable results. However, good log-based TOC quantifications can be achieved by taking the median average of TOC estimates from several indicators. Many shale reservoirs contain 10 wt% pyrite and total organic carbon (TOC), which translates to 7% pyrite and 20% kerogen by volume. High volumetric percentages of pyrite and kerogen significantly affect the rock grain density. In low-porosity shale reservoirs, each 0.02 g/cm error in grain density produces approximately 1 p.u. error in porosity. Pyrite is commonly present in organic-rich shale intervals of shale gas formations because of the reducing conditions that enhanced organic matter preservation, and it may play a role in decreased resistivity response if the volume is sufficient. Consequently, in shale reservoirs, any method of predicting TOC using resistivity logs, such as DeltaLogR, should also consider the presence of pyrite. Similarly, TOC predictions based on bulk-density logs may also be sensitive to elevated pyrite concentrations. The link between pyrite presence and the depositional environment for many organic-rich shale reservoirs suggests that pyrite and sulfur may be useful TOC indicators in some situations. This paper examines the possible application of pyrite and sulfur for predicting TOC in shale reservoirs, such as in the Haynesville shale reservoir, but results should be applicable to many other shale reservoirs. An interesting result is that, although it may be possible to calibrate a TOC-based pyrite indicator for individual wells, the calibration is not universally applicable.
- North America > United States > Texas (1.00)
- North America > United States > Louisiana (1.00)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock > Shale (1.00)
- Geology > Mineral > Sulfide > Iron Sulfide > Pyrite (1.00)
- Materials > Metals & Mining (1.00)
- Energy > Oil & Gas > Upstream (1.00)
- North America > United States > Texas > Haynesville Shale Formation (0.99)
- North America > United States > Louisiana > Haynesville Shale Formation (0.99)
- North America > United States > Louisiana > Haynesville Formation (0.99)
- North America > United States > Arkansas > Haynesville Shale Formation (0.99)
Characterizing A Turbiditic Reservoir
Daggett, Paul (Pioneer Natural Resources) | Knutson, Craig (Pioneer Natural Resources) | Cook, Robert (Pioneer Natural Resources) | Chemali, Roland (Halliburton) | Quirein, John (Halliburton) | Shokeir, Ramez (Halliburton) | Burinda, Bryan (Halliburton) | Pitcher, Jason (Halliburton)
ABSTRACT: The oil producing horizon subject of this publication includes the hydrocarbon-bearing turbiditic interval. The characterization of this horizon and the assessment of the associated reserves are conducted largely through detailed petrographic analyses of a vertical core traversing the reservoir, with a complete suite of wireline logs in a vertical well and with selected logging-while-drilling (LWD) logs in high angle wells. Horizontal layering in the subject reservoir is evident on core photos and on electrical images obtained with both wireline and LWD logs. The layered structure creates a significant electrical anisotropy with vertical resistivity being several folds larger than horizontal resistivity. The evaluation of the formation is then subdivided into two major steps. First, an accurate determination of both vertical and horizontal resistivity across the interval of interest is conducted from high angle wells. Various inversion methods are compared using advanced wave resistivity technology. Second, the computation of oil saturation in the non-shaly interval is performed, based on electrical anisotropy, using a modified Thomas-Stieber method. A key component of the method lies in the understanding of the intrinsic anisotropy of the interbedded shale laminae. The article compares the various approaches used in this field for determining vertical resistivity and horizontal resistivity. No 3D wireline induction log was run. The best overall results are obtained with advanced LWD sensors run in high angle wells. The computed hydrocarbon content obtained from the modified Thomas-Stieber method is compared to the core results from the nearby vertical well. The agreement between them confirms the overall validity of the measurement and method. INTRODUCTION Several fields of the Colville High, North Slope region of Alaska have been studied during recent decades to gain better petrophysical understanding of the laminated structure of some of the reservoirs. That activity extended along three main avenues.
- Geology > Geological Subdiscipline (0.88)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock > Shale (0.38)
- Geophysics > Borehole Geophysics (1.00)
- Geophysics > Seismic Surveying > Seismic Modeling (0.40)
- North America > United States > Alaska > North Slope Basin > Umiat-Gubik Area > Torok Formation (0.99)
- North America > United States > Alaska > North Slope Basin > Kuparuk River Field > Kuparuk Field (0.99)
ABSTRACT: This paper reviews and compares three recently published approaches for simplicity, validity, and parameter sensitivity. The first two approaches are based on deterministic models; the third approach uses a response equation technique in which models are defined by means of tool response equations and interpretation constraint equations. The first approach assumes that the weight fraction total organic carbon (TOC) is available from an external source, the rock grain density is known, and total water saturation is constant. This enables for the first approach the use of a single equation based upon the bulk density log to solve for total porosity from which the gas-filled porosity can be obtained with the assumption of constant water saturation. The second approach assumes that the formation consists of two constituents: porous mineral matrix and porous kerogen. It makes use of the fact that in gas shale, kerogen generally contains oil-wet porosity, so that constant kerogen porosity, completely gas saturated, is imposed. The volumes of porous mineral matrix, porous mineral kerogen, and porous mineral porosity can be obtained by using the sonic and density logs with an assumed known rock grain density and assuming the porous mineral matrix gas saturation is a constant. The assumption of constant porous mineral gas saturation can be relaxed by iteratively using the resistivity log to update the assumed value of the hydrocarbon saturation. This paper shows that Methods 1 and 2 can be replicated by using a response equation based statistical optimization technique. This technique requires some simple constraints, such as constant kerogen porosity or constant gas saturation. Moreover, the constant saturation assumptions can be easily removed, and it is possible to calibrate to core grain density and gas-filled porosity with or without wireline geochemical data, TOC, or x-ray diffraction (XRD) mineral data.
- Geology > Geological Subdiscipline > Geochemistry (1.00)
- Geology > Mineral > Silicate (0.70)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock > Mudrock > Shale (0.64)
- Geology > Petroleum Play Type > Unconventional Play > Shale Play > Shale Gas Play (0.46)
- North America > United States > Texas > Haynesville Shale Formation (0.99)
- North America > United States > Texas > Fort Worth Basin > Barnett Shale Formation (0.99)
- North America > United States > Louisiana > Haynesville Shale Formation (0.99)
- (11 more...)