Geologic pore system characterization framework

A system, comprising:

• a processor;
• memory accessible to the processor;
• and
• processor-executable instructions stored in the memory and executable by the processor to instruct the system to:
• acquire nuclear magnetic resonance (NMR) data and sonic data for a borehole in a subsurface geologic region using a tool string disposed in the borehole;
• determine, from the sonic data by inverting an effective medium rock physics model using acoustic compressional and shear measurements:
• volume fractions of crack pores, reference pores, and stiff pores;
• and
• pore aspect ratios for the crack pores, the reference pores, and the stiff pores;
• determine, from the NMR data, micro porosity and macro porosity by NMR factor analysis or Classification and Inversion of Pore-scale Hydrogen Environments for Reservoir evaluation (CIPHER) processing;
• jointly invert the NMR data and the sonic data, using the volume fractions of the crack pores, the reference pores, and the stiff pores and using the micro porosity and the macro porosity, to determine volume fractions for six pore groups comprising micro crack, micro reference, micro stiff, macro crack, macro reference, and macro stiff;
• compute a T2 logarithmic mean for the micro porosity and a T2 logarithmic mean for the macro porosity;
• compute a pore surface area-to-volume ratio for micro pores and a pore surface area-to-volume ratio for macro pores from the T2 logarithmic mean for the micro porosity and the T2 logarithmic mean for the macro porosity;
• compute, for each of the six pore groups, pore geometry parameters comprising a semi-long axis, a semi-short axis, and a cross-section area index using the pore aspect ratios and the pore surface area-to-volume ratios, the computing the semi-long axis, the semi-short axis, and the cross-section area index comprising using an oblate spheroid geometric model;
• determine regression coefficients by performing regression using core permeability data with total porosity, the volume fractions of the six pore groups, and the cross-section area index for the six pore groups;
• compute, using the regression coefficients, permeability values with respect to depth along at least a portion of the borehole;
• and
• control movement of the tool string in the at least a portion of the borehole based at least in part on the computed permeability values.

One or more computer-readable media comprising computer-executable instructions executable by a system to instruct the system to:

• acquire nuclear magnetic resonance (NMR) data and sonic data for a borehole in a subsurface geologic region using a tool string disposed in the borehole;
• determine, from the sonic data by inverting an effective medium rock physics model using acoustic compressional and shear measurements:
• volume fractions of crack pores, reference pores, and stiff pores;
• and
• pore aspect ratios for the crack pores, the reference pores, and the stiff pores;
• determine, from the NMR data, micro porosity and macro porosity by NMR factor analysis or Classification and Inversion of Pore-scale Hydrogen Environments for Reservoir evaluation (CIPHER) processing;
• jointly invert the NMR data and the sonic data, using the volume fractions of the crack pores, the reference pores, and the stiff pores and using the micro porosity and the macro porosity, to determine volume fractions for six pore groups comprising micro crack, micro reference, micro stiff, macro crack, macro reference, and macro stiff;
• compute a T2 logarithmic mean for the micro porosity and a T2 logarithmic mean for the macro porosity:
• compute a pore surface area-to-volume ratio for micro pores and a pore surface area-to-volume ratio for macro pores from the T2 logarithmic mean for the micro porosity and the T2 logarithmic mean for the macro porosity;
• compute, for each of the six pore groups, pore geometry parameters comprising a semi-long axis, a semi-short axis, and a cross-section area index using the pore aspect ratios and the pore surface area-to-volume ratios, the computing the semi-long axis, the semi-short axis, and the cross-section area index comprising using an oblate spheroid geometric model;
• determine regression coefficients by performing regression using core permeability data with total porosity, the volume fractions of the six pore groups, and the cross-section area index for the six pore groups;
• compute, using the regression coefficients, permeability values with respect to depth along at least a portion of the borehole;
• and
• control movement of the tool string in the at least a portion of the borehole based at least in part on the computed permeability values.