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Summary The quantitative integration of nuclear measurements into the in-situ petrophysical and geophysical interpretation of rock formation has been difficult because of the lack of efficient algorithms to simulate them. We introduce and successfully implement a new method for rapid simulation of borehole neutron measurements using Monte Carlo-derived spatial flux sensitivity functions (FSFs) and diffusion flux-difference (DFD) approximations. The method calculates spatial sensitivity flux perturbations using flux-difference approximations of one-group neutron diffusion models. With appropriate boundary conditions, we implement the one-group, time-independent neutron diffusion solution for non-multiplying systems in cylindrical coordinates. The solution is differentiated with respect to neutron cross-section, thereby yielding an expression for flux-difference due to cross-section perturbations. Constant transport-correction factors for cross-section parameters in the diffusion model are calculated with a flux-fitting method. Thereafter, spatial responses are rapidly and accurately calculated using a first-order Rytov diffusion flux-difference (DFD) approximation. Examples of application indicate that neutron porosity logs can be efficiently simulated with the new method even in complex geometrical and physical conditions, with errors lower than 2.5 porosity units (p.u.) in highly-deviated wells.
Inversion-based method for interpretation of logging-while-drilling density measurements acquired in high-angle and horizontal wells
Mendoza, Alberto (The University of Texas) | Ijasan, Olabode (The University of Texas) | Torres-Verdín, Carlos (The University of Texas) | Preeg, William E. | Rasmus, John (Schlumberger) | Radtke, R. J. (Schlumberger) | Stockhausen, Edward (Chevron ETC)
ABSTRACT We introduce a sector-based inversion method to improve the petrophysical interpretation of logging-while-drilling density measurements acquired in high-angle and horizontal wells. The central objective is to reduce shoulder-bed effects on the measurements. This approach is possible because of a recently developed technique to accurately and efficiently simulate borehole density measurements. The inversion-based interpretation method consists of first detecting bed boundaries from short-spacing detector or bottom-quadrant compensated density by calculating their variance, representative of the measurement inflection point, within a sliding window. Subsequently, a correlation algorithm calculates dip and azimuth from the density image. Depth shifts that vary azimuthally and depend on relative dip angle, together with the effective penetration length of each sensor, refine previously selected bed boundaries. Next, the inversion method combines sector-based density measurements acquired at all measurement points along the well trajectory to estimate layer-by-layer densities. In the presence of standoff, the method excludes upper sectors most affected by standoff to reduce inaccuracies due to borehole mud. To verify the reliability and applicability of the inversion method, we first use forward simulations to generate synthetic density images for a model constructed from field data. Results indicate that inversion improves the interpretation of azimuthal density data as it consistently reduces shoulder-bed effects. Inversion results obtained from field measurements are appraised by quantifying the corresponding integrated porosity-meter yielded by inversion methods in comparison to standard techniques that use simple cutoffs on field-processed compensated density. Integrated porosity-meter of inverted synthetic density measurements increases by 4.6% with respect to noninverted field measurements. Also, integrated porosity-meter obtained from inversion results that include only bottom sectors improved by 65.4% with respect to that calculated with field-compensated, bottom-quadrant density measurements.
- Geology > Geological Subdiscipline > Stratigraphy (0.68)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock (0.46)