Developing templates for integrating quantitative geophysics and hydraulic fracture completions data: Part I ‐ Principles and theory

Perez, Marco; Close, David; Goodway, Bill; Purdue, Greg

doi:10.1190/1.3627553

Cited by 11 publications

(8 citation statements)

References 8 publications

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“…Goodway et al (1997) and Perez (2011) present λρ-μρ lithology templates, which have been very useful for reservoir characterization and correlating brittleness to rock properties. Goodway et al (2010) use these templates to estimate the minimum closure stress from seismic estimates of λρ and μρ.…”

Section: Poisson's Ratio Versus Young's Modulus Brittleness Crossplotsmentioning

confidence: 99%

“…The cut-off depends on the shale play in which it is applied and on the expertise of the interpreter. Perez (2011) combines λρ-μρ seismic logs with production data to create templates that can be applied to better understand the parameters that control the estimated ultimate recovery (EUR) and stimulated rock volume in unconventional reservoirs. In the case of stimulated volumes, the templates show the variation in λρ-μρ for a combination of mineralogical mixtures (quartz and clay) versus total and effective porosity.…”

Section: Introductionmentioning

confidence: 99%

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Mineralogy-based brittleness prediction from surface seismic data: Application to the Barnett Shale

2014

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Differentiating brittle and ductile rocks from surface seismic data is the key to efficient well location and completion. Brittleness average estimates based only on elastic parameters are easy to use but require empirical calibration. In contrast, brittleness index (BI) estimates are based on mineralogy laboratory measurements and, indeed, cannot be directly measured from surface seismic data. These two measures correlate reasonably well in the quartz-rich Barnett Shale, but they provide conflicting estimates of brittleness in the calcite-rich Viola, Forestburg, Upper Barnett, and Marble Falls limestone formations. Specifically, the BI accurately predicts limestone formations that form fracture barriers to be ductile, whereas the brittleness average does not. We used elemental capture spectroscopy and elastic logs measured in the same cored well to design a 2D λρ-μρ to brittleness template. We computed λρ and μρ volumes through prestack seismic inversion and calibrate the results with the λρ-μρ template from well logs. We then used microseismic event locations from six wells to calibrate our prediction, showing that most of the microseismic events occur in the brittle regions of the shale, avoiding more ductile shale layers and the ductile limestone fracture barriers. Our λρ-μρ to brittleness template is empirical and incorporates basin-and perhaps even survey-specific correlations of mineralogy and elastic parameters through sedimentation, oxygenation, and diagenesis. We do not expect this specific template to be universally applicable in other mudstone rock basins; rather, we recommend interpreters generate similar site-specific templates from logs representative of their area, following the proposed workflow.

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Section: Poisson's Ratio Versus Young's Modulus Brittleness Crossplotsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Mineralogy-based brittleness prediction from surface seismic data: Application to the Barnett Shale

2014

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“…Figure 5. Heuristic template to interpret seismic, well log, or laboratory rock properties in terms of EUR, Original gas in place (OGIP), recovery factor (RF), pore pressure, and fracture density (Perez et al, 2011). 20%, but the underlying principles can easily be extended to interpretation in other shales with differing compositions. We provide a brief overview of their approach that we have adopted in this work.…”

Section: Methodsmentioning

confidence: 99%

“…In Perez et al (2011), a workflow based on "heuristic" rock physics templates ( Figure 5) was developed to guide the interpretation of seismically inverted properties in unconventional reservoirs. The shale reported in their study varies in composition from 60/40% quartz/ clay to 100% quartz and porosity ranges from 0% to Table 1.…”

Section: Methodsmentioning

confidence: 99%

“…Studies by Kale (2009) and Gao (2011) are centered on petrophysical characterization and rock-typing based on cores and well log information. Singh (2008) instead relied on well logs to generate stratigraphic cross sections of the Barnett shale along with classification of the shale into 10 lithofacies, while Perez et al (2011) generated templates for shales of varying compositions and porosities based on seismic-derived rock properties to enable targeting the most productive volumes of the reservoir which are also most conducive to hydraulic fracture stimulation.…”

Section: Introductionmentioning

confidence: 99%

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Integration of surface seismic, microseismic, and production logs for shale gas characterization: Methodology and field application

Alzate

Devegowda

2013

Interpretation

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Technologies such as horizontal drilling and multistage hydraulic fracturing are central to ensuring the viability of shale oil and gas resource development by maximizing contact with the most productive reservoir volumes. However, characterization efforts based on the use of well logs and cores, although very informative, may be associated with substantial uncertainty in interwell volumes. Consequently, this work is centered around the development of a predictive tool based on surface seismic data analysis to rapidly demarcate the most prolific reservoir volumes, to identify zones more amenable to hydraulic fracturing, and to provide a methodology to locate productive infill wells for further development. Specifically, we demonstrate that surface seismic attributes such as λρ/μρ crossplots can successfully be employed to quantitatively grade reservoir rocks in unconventional plays. We also investigate the role of seismically inverted Poisson's ratio as a fracability discriminator and Young's modulus as an indicator of total organic carbon richness and porosity. The proposed predictive tool for sweet spot identification relies on classifying reservoir volumes on the basis of their amenability to fracturing and reservoir quality. The classification scheme is applied to a field case study from the Lower Barnett Shale and we validate these results using production logs recorded in four horizontal wells and microseismic data acquired while fracturing these wells. The integration of seismic data, production logs, and microseismic data underscores the value of shale reservoir characterization with a diverse suite of measurements to determine optimal well locations and to locate hydraulic fracture treatments. A key advantage of the methodology developed here is the ease of regional-scale characterization that can easily be generalized to other shale plays.

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Rock physics model of tight oil siltstone for seismic prediction of brittleness

Tan

Müller

et al. 2020

Geophysical Prospecting

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Tight oil siltstones are rocks with complex structure at pore scale and are characterized by low porosity and low permeability at macroscale. The production of tight oil siltstone reservoirs can be increased by hydraulic fracturing. For optimal fracking results, it is desirable to map the ability to fracture based on seismic data prior to fracturing. Brittleness is currently thought to be a key parameter for evaluating the ability to fracture. To link seismic information to the brittleness distribution, a rock physics model is required. Currently, there exists no commonly accepted rock physics model for tight oil siltstones. Based on the observed correlation between porosity and mineral composition and known microstructure of tight oil siltstone in Daqing oilfield of Songliao basin, we develop a rock physics model by combining the Voigt–Reuss–Hill average, self‐consistent approximation and differential effective medium theory. This rock physics model allows us to explore the dependence of the brittleness on porosity, mineral composition, microcrack volume fraction and microcrack aspect ratio. The results show that, as quartz content increases and feldspar content decreases, Young's modulus tends to increase and Poisson ratio decreases. This is taken as a signature of higher brittleness. Using well log data and seismic inversion results, we demonstrate the versatility of the rock physics template for brittleness prediction.

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Developing templates for integrating quantitative geophysics and hydraulic fracture completions data: Part I ‐ Principles and theory

Cited by 11 publications

References 8 publications

Mineralogy-based brittleness prediction from surface seismic data: Application to the Barnett Shale

Mineralogy-based brittleness prediction from surface seismic data: Application to the Barnett Shale

Integration of surface seismic, microseismic, and production logs for shale gas characterization: Methodology and field application

Rock physics model of tight oil siltstone for seismic prediction of brittleness

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