Rock-physics analysis of clay-rich source rocks on the Norwegian Shelf

AbstractIn unconventional reservoirs, the pore space is hosted by a heterogeneous matrix with various minerals and organic components. This heterogeneity complicates petrophysical interpretation during hydrocarbon exploration. A digital rock physics study of thermal and electrical conductivity was conducted using high-resolution focused ion beam scanning electron microscopy images of carbonate-rich source rocks. Finite-volume simulation results are discussed in context of the sample heterogeneity and anisotropy and supported by comparisons to empirical equations and effective medium theory. The results show how the presence of organic matter, pyrite, and pore constrictions impacts application of empirical equations and simplified models to unconventional reservoirs. Graphic abstract

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Petrophysical Rock Typing in Organic-Rich Source Rocks Using Well Logs

10.1190/urtec2013-117 ◽

2013 ◽

Cited By ~ 2

Author(s):

Alvaro Aranibar ◽

Mehrnoosh Saneifar ◽

Zoya Heidari

Keyword(s):

Rich Source ◽

Source Rocks ◽

Well Logs ◽

Rock Typing

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Evolution of organo-clay composites with respect to thermal maturity in type II organic-rich source rocks

Geochimica et Cosmochimica Acta ◽

10.1016/j.gca.2016.09.008 ◽

2016 ◽

Vol 195 ◽

pp. 68-83 ◽

Cited By ~ 18

Author(s):

Jeremie Berthonneau ◽

Olivier Grauby ◽

Muhannad Abuhaikal ◽

Roland J.-M. Pellenq ◽

Franz J. Ulm ◽

...

Keyword(s):

Rich Source ◽

Source Rocks ◽

Type Ii ◽

Thermal Maturity ◽

Organo Clay

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Lacustrine conditions control on the distribution of organic-rich source rocks: An instance analysis of the lower 1st member of the Shahejie Formation in the Raoyang Sag, Bohai Bay Basin

Journal of Natural Gas Science and Engineering ◽

10.1016/j.jngse.2020.103320 ◽

2020 ◽

Vol 78 ◽

pp. 103320

Author(s):

Jie Yin ◽

Fang Hao ◽

Zhenqi Wang ◽

Xiaoyan Chen ◽

Huayao Zou

Keyword(s):

Rich Source ◽

Source Rocks ◽

Bohai Bay ◽

Bohai Bay Basin ◽

Shahejie Formation ◽

Instance Analysis

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Computing elastic properties of organic-rich source rocks using digital images

The Leading Edge ◽

10.1190/tle40090662.1 ◽

2021 ◽

Vol 40 (9) ◽

pp. 662-666

Author(s):

Mita Sengupta ◽

Shannon L. Eichmann

Keyword(s):

Organic Matter ◽

Elastic Properties ◽

Focused Ion Beam ◽

Ion Beam ◽

Rock Physics ◽

Flow Property ◽

Source Rocks ◽

Digital Rock ◽

Rock Structure ◽

Imaging Resolution

Digital rocks are 3D image-based representations of pore-scale geometries that reside in virtual laboratories. High-resolution 3D images that capture microstructural details of the real rock are used to build a digital rock. The digital rock, which is a data-driven model, is used to simulate physical processes such as fluid flow, heat flow, electricity, and elastic deformation through basic laws of physics and numerical simulations. Unconventional reservoirs are chemically heterogeneous where the rock matrix is composed of inorganic minerals, and hydrocarbons are held in the pores of thermally matured organic matter, all of which vary spatially at the nanoscale. This nanoscale heterogeneity poses challenges in measuring the petrophysical properties of source rocks and interpreting the data with reference to the changing rock structure. Focused ion beam scanning electron microscopy is a powerful 3D imaging technique used to study source rock structure where significant micro- and nanoscale heterogeneity exists. Compared to conventional rocks, the imaging resolution required to image source rocks is much higher due to the nanoscale pores, while the field of view becomes smaller. Moreover, pore connectivity and resulting permeability are extremely low, making flow property computations much more challenging than in conventional rocks. Elastic properties of source rocks are significantly more anisotropic than those of conventional reservoirs. However, one advantage of unconventional rocks is that the soft organic matter can be captured at the same imaging resolution as the stiff inorganic matrix, making digital elasticity computations feasible. Physical measurement of kerogen elastic properties is difficult because of the tiny sample size. Digital rock physics provides a unique and powerful tool in the elastic characterization of kerogen.

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Lithofacies-dependent rock physics templates of an unconventional shale reservoir on the North Slope, Alaska

Interpretation ◽

10.1190/int-2019-0156.1 ◽

2020 ◽

pp. 1-49

Author(s):

Minh Tran ◽

Tapan Mukerji ◽

Allegra Hosford Scheirer

Keyword(s):

Organic Carbon ◽

Total Organic Carbon ◽

Source Rock ◽

Velocity Ratio ◽

Rock Physics ◽

Hydrogen Index ◽

Source Rocks ◽

Rock Properties ◽

North Slope ◽

Petrophysical Properties

Over the past 20 years, oil and gas companies have turned their attention to producing petroleum directly from organic-rich shale. Successful exploration, appraisal, and production strategies for source rocks critically depend on reliable identification of their organic components (kerogen, in particular) and generation potential. There is mounting demand to evaluate organic richness in terms of quantity (i.e. total organic carbon) and quality (i.e. hydrogen index) from seismic data, which is usually the only source of information in the early development period of emerging shale plays. We delineated major seismic lithofacies on the Alaska North Slope using elastic, seismic, and petrophysical properties. We performed a well-established quantitative seismic interpretation workflow to integrate geochemical data in the lithofacies definition. Rock physics templates of seismic parameters, Acoustic Impedance, (AI), versus P-wave to S-wave velocity ratio, (VP/VS), are constructed for each lithofacies to assess variations in pore fluid and lithology. We proposed correlations between source rock properties (hydrogen index, total organic carbon) and petrophysical properties (bulk density, porosity, sonic velocity ratio) of the major lithofacies. These correlations, together with facies-specific rock physics templates, can be utilized to predict organic richness and source rock properties away from drilled wells. The models are validated by training data from 2 regional wells to observe their applicability on the Alaska North Slope.

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