Application of an Integrated Petrophysical Modeling to Improve Log Based Reservoir Characterization and Oil In-Place Estimate of a Fresh Water Shaly Sand Reservoir
- Sushanta Bose (WD Von Gonten & Company) | Michael T. Myers (University of Houston) | Peila Chen (University of Houston) | Ganesh Thakur (University of Houston)
- Document ID
- Society of Petrophysicists and Well-Log Analysts
- SPWLA 60th Annual Logging Symposium, 15-19 June, The Woodlands, Texas, USA
- Publication Date
- Document Type
- Conference Paper
- 2019. held jointly by the Society of Petrophysicists and Well Log Analysts (SPWLA) and the submitting authors
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- 97 since 2007
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We describe the application of a joint low resistivity and saturation height model for analyzing the log measured resistivity of a fresh water shaly sand. Two lithologies were identified: thin beds with relatively clean interbedded sands and massive sands containing significant amounts of dispersed and structural clays. This discrimination using a Thomas-Stieber analysis, allows for improved estimation of saturations and identifying locations of bypassed pay.
Laboratory-measured reservoir core plug porosities range 20-31% and permeability varies between 130 and 4500mD. As much as 30% of the measured porosity is microporosity associated with clay minerals. Rock quality index (RQI) and flow zone indicator (FZI) values were combined with thin section, CT scan, and mercury injection capillary pressure (MICP) data to define four rock types. The XRD and thin section analysis showed clay content of up to 20% bulk volume with kaolinite as the dominant clay type. In the shaly zones which contain Fe-rich minerals, the grain density is significantly higher. The measured Co-Cw data indicate cation-exchange-capacity (CEC) values of up to 0.08 meq/gm, consistent with typical values for kaolinite. The measured formation water resistivity (Rw) is ∼0.82-ohmm (∼3,000 ppm NaCl). It is this low brine salinity that requires the use of a shaly-sand model.
Examination of thin section, core, and XRD indicates that the western area of the reservoir is characterized by laminated sands while the eastern area is dominated by massive sands containing only dispersed and structural clay.
A laminated clay resistivity model with parallel conductors (shale layers and Archie-sands) was developed for the western area. Net-to-gross (NTG) for the laminated sand was estimated from the Thomas-Stieber plot, and conductivity of the shale layers was assessed using a conductivity-NTG cross-plot. This cross-plot was used to calculate the relative contributions to the conductivity from the shale layers, and allowed direct estimation of water saturation in the interbedded sands.
The eastern area sands contain varying amounts of dispersed and structural clays. A Waxman-Smits model was therefore applied. The cleanest sands are characterized by high porosity and permeability. The economics of these sands are however challenged by a rapid increase in water-cut, interpreted to be due to sand-streaks of high porosity and high permeability.
Leverett J-function based saturation height functions (SHFs) were also generated for the four different rock types. The connate water saturation estimated from the SHF and the log-based resistivity model are both approximately 15% in the best quality rock and at 20% for the medium quality rock.
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