The potential of nuclear magnetic resonance (NMR logging for evaluating low-resistivity reservoirs has been recognized for several years. The most commonly used methods typically involved acquisition of two NMR measurements in which either the wait time or echo spacing only was varied. Interpretation methods relied on assumptions concerning fluid NMR responses, and analysis was limited to single depths of investigation (DOIs regardless of acquisition details. However, there is a growing body of evidence indicating that fluid saturations can vary significantly over the range of DOIs sensed by modern NMR logging tools, especially in wells drilled with oil-based mud (OBM. Current-generation NMR logging tools now allow acquisition of comprehensive multidimensional measurement suites at multiple DOIs. Combined with robust model-independent inversion techniques, these data allow detection and quantification of hydrocarbons without prior knowledge of fluid responses. By treating each DOI independently, invasion effects are properly accounted for and more-accurate fluid saturations can be derived. This paper discusses the application of two new NMR methods and the density magnetic resonance porosity (DMRP method for identifying gas and estimating the in situ gas volume in low-resistivity and low-contrast reservoirs. The first is a comprehensive fluid characterization mode that measures molecular diffusion rates, T2, and T1 relaxation times independently at two DOIs. The second mode uses high-resolution (HR NMR measurements to detect thin beds that might be overlooked by lower resolution measurements. The HR mode also invokes two DOIs and uses different polarization times to assist in detecting light hydrocarbons. The third method uses density and NMR porosity to estimate the volume of porosity and gas saturation in the flushed zone. A number of field examples are presented showing the value of the three procedures in gas-bearing shaly sand formations. In each case, saturations derived from NMR are compared with traditional resistivity-based analysis. Where available, pressure and sampling data are used to validate results.
Low-Resistivity Pay Evaluation Using Multidimensional And High-Resolution Magnetic Resonance Profiling
Guru, Udit, Heaton, Nicholas, Bachman, H. Nate, LaVigne, Jack, and Walid A. Ahmed. "Low-Resistivity Pay Evaluation Using Multidimensional And High-Resolution Magnetic Resonance Profiling." Paper presented at the SPWLA 46th Annual Logging Symposium, New Orleans, Louisiana, June 2005.
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