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TitlePore pressure prediction and brittleness index estimation from well logs for identifying sweet spots
AuthorLiu, Y; Chen, Z
Alt SeriesEarth Sciences Sector, Contribution Series 20140389
PublisherGeoConvention
MeetingGeoConvention 2015; Calgary; CA; May 4-8, 2015
Documentserial
Lang.English
Mediapaper; on-line; digital
File formatpdf
Subjectspetroleum resources; shale, commodity; shales; gas; gas wells; reservoir pressures; productivity; clay minerals; organic materials; Duvernay Shale; shale brittleness; Devonian
ProgramShale-hosted petroleum ressource assesment, Geoscience for New Energy Supply (GNES)
LinksOnline - En ligne
AbstractResource occurrence in shale reservoir is pervasive, but commercial production from shale reservoirs requires extensive artificial stimulation. Therefore shale gas development is characterized with low geological risk, but high commercial production risk. As wellhead price for natural gas stays low, economic margin of shale gas development could be thin and early identification of sweet spot is crucial to economic success. Study from North American shale gas development suggests that a static sweet spot of high resource abundance may not be necessarily coincident with a dynamic sweet spot of high productivity. In addition to resource abundance and reservoir quality, shale brittleness and reservoir pressure could be the other two major geological factors that affect productivity. In our recent efforts of shale gas resource characterization, well logs and seismic data are used to help identify the dynamic sweet spots. This paper discusses the use of petrophysical data to estimate shale brittleness and predict formation pressure. In a separate paper ¿Identify shale gas sweet spots from seismic data¿, an effort is made to tackle the problem from the perspective of seismic processing.
In this study, we propose a petrophysical model that consists of four components, i.e., non-clay grains, clay minerals, organic matter and porosity and use it to represent the shale reservoir volume. The Eaton equation was applied to calculate the pore pressure from sonic logs, and Passey method (Passey et al., 1990) or support vector regression statistical methods (Liu et al., 2013) was employed to estimate TOC. An inverse-distance weighted method was then utilized to evaluate mineral compositions after correcting the impacts of clay mineral and kerogen contents on the well responses. Finally the brittleness index was estimated based on mineral compositions and geomechanical properties derived from dipole sonic log for wells that data are available. The potential dynamic sweet spots could be the area with high resource abundance, high brittleness index and high pore pressure. This paper discusses the petrophysical model, mineral composition estimation using the proposed inversed distance method, shale brittleness index estimation from dipole sonic data, and the relationship between the estimated mineral compositions and rock brittleness through examples from the Devonian Duvernay Shale in the Western Canadian Sedimentary Basin.
Summary(Plain Language Summary, not published)
Shale gas development is characterized by low geological risk, but high commercial production risk. In this study, we propose a petrophysical model to help identify sweet spots using petrophysical data. The potential dynamic sweet spots could be the area with high resource abundance, high brittleness index and high pore pressure. This paper discusses the petrophysical model, mineral composition estimation, shale brittleness index estimation from dipole sonic data, and the relationship between mineral composition and rock brittleness through examples from the Devonian Duvernay Shale in the Western Canadian Sedimentary Basin.
GEOSCAN ID295730