Spelling suggestions: "subject:"more types"" "subject:"more mypes""
1 |
Quantitative assessment of pore types and pore size distribution across thermal maturity, Eagle Ford Formation, South TexasPommer, Maxwell Elliott 09 September 2014 (has links)
Scanning electron microscopy of Ar-ion milled samples from the Eagle Ford Formation, South Texas shows that the character and abundance of porosity changes significantly across burial conditions as a result of compaction, cementation, bitumen generation, and generation of secondary porosity within organic matter (OM). Samples displaying a range of compositions and maturities are imaged and quantified to provide insight into the effects of these processes. Porosity in low-maturity samples (Ro~0.5%) is volumetrically dominated (0.1% -12.5% bulk volume, average 6.2%) by relatively large, mostly interparticle, primary mineral-associated pores (median sizes range 35.9-52.7 nm). Larger pores are generally associated with coccolith debris that is commonly aggregated into pellets. Porosity and pore size correlate directly with calcite abundance and inversely with OM volumes. OM is dominantly detrital kerogen "stringers" that range in size and have spatial distributions and character suggestive of detrital origin. Destruction of primary porosity in low-maturity samples has occurred due to compaction of ductile kerogen and clays and, to a minor degree, as a result of cementation and infill of early bitumen. Smaller, secondary OM-hosted pores (median size range 11.1-14.9 nm) volumetrically dominate porosity (0.02%-3.6% bulk volume, average of 1.36%), in most high-maturity samples (Ro~1.2%-1.3%). Mineral-associated pores are present, but are typically smaller (median size range from 20.3-40.6 nm) and less abundant (0.0%-10.0% bulk volume, average of 2.5%) than at low maturity. Abundant mineral-associated porosity is present locally in samples where incursion of primary pore space by bitumen has not occurred. OM within high-maturity samples is distributed more evenly throughout the rock fabric, occupying spaces similar in size and morphology to primary interparticle pores, coating euhedral crystals (probable cements), and filling intraparticle porosity. These observations, and positive correlation between calcite and OM volumes (OM-hosted pore volume included) in samples with dominantly OM-hosted pore networks, suggests that a large portion of OM within high-maturity samples is diagenetic in origin and has filled primary pore space. Destruction of primary porosity in high-maturity samples has occurred through cementation, bitumen infill, and, possibly greater compaction. Additional porosity, however, has been generated through maturation of OM. / text
|
2 |
Relationship between pore geometry, measured by petrographic image analysis, and pore-throat geometry, calculated from capillary pressure, as a means to predict reservoir performance in secondary recovery programs for carbonate reservoirs.Dicus, Christina Marie 15 May 2009 (has links)
The purpose of this study was first to develop a method by which a detailed
porosity classification system could be utilized to understand the relationship between
pore/pore-throat geometry, genetic porosity type, and facies. Additionally, this study
investigated the relationships between pore/pore-throat geometry, petrophysical
parameters, and reservoir performance characteristics. This study focused on the
Jurassic Smackover reservoir rocks of Grayson field, Columbia County, Arkansas.
This three part study developed an adapted genetic carbonate pore type
classification system, through which the Grayson reservoir rocks were uniquely
categorized by a percent-factor, describing the effect of diagenetic events on the
preservation of original depositional texture, and a second factor describing if the most
significant diagenetic event resulted in porosity enhancement or reduction. The second
part used petrographic image analysis and mercury-injection capillary pressure tests to
calculate pore/pore-throat sizes. From these data sets pore/pore-throat sizes were
compared to facies, pore type, and each other showing that pore-throat size is controlled by pore type and that pore size is controlled primarily by facies. When compared with
each other, a pore size range can be estimated if the pore type and the median pore-throat
aperture are known.
Capillary pressure data was also used to understand the behavior of the
dependent rock properties (porosity, permeability, and wettability), and it was
determined that size-reduced samples, regardless of facies, tend to show similar
dependent rock property behavior, but size-enhanced samples show dispersion. Finally,
capillary pressure data was used to understand fluid flow behavior of pore types and
facies. Oncolitic grainstone samples show unpredictable fluid flow behavior compared
to oolitic grainstone samples, yet oncolitic grainstone samples will move a higher
percentage of fluid. Size-enhanced samples showed heterogeneous fluid flow behavior
while the size-reduced samples could be grouped by the number of modes of pore-throat
sizes.
Finally, this study utilized petrographic image analysis to determine if 2-
dimensional porosity values could be calculated and compared to porosity values from
3-dimensional porosity techniques. The complex, heterogeneous pore network found in
the Grayson reservoir rocks prevents the use of petrographic image analysis as a porosity
calculation technique.
|
3 |
Relationship between pore geometry, measured by petrographic image analysis, and pore-throat geometry, calculated from capillary pressure, as a means to predict reservoir performance in secondary recovery programs for carbonate reservoirs.Dicus, Christina Marie 10 October 2008 (has links)
The purpose of this study was first to develop a method by which a detailed
porosity classification system could be utilized to understand the relationship between
pore/pore-throat geometry, genetic porosity type, and facies. Additionally, this study
investigated the relationships between pore/pore-throat geometry, petrophysical
parameters, and reservoir performance characteristics. This study focused on the
Jurassic Smackover reservoir rocks of Grayson field, Columbia County, Arkansas.
This three part study developed an adapted genetic carbonate pore type
classification system, through which the Grayson reservoir rocks were uniquely
categorized by a percent-factor, describing the effect of diagenetic events on the
preservation of original depositional texture, and a second factor describing if the most
significant diagenetic event resulted in porosity enhancement or reduction. The second
part used petrographic image analysis and mercury-injection capillary pressure tests to
calculate pore/pore-throat sizes. From these data sets pore/pore-throat sizes were
compared to facies, pore type, and each other showing that pore-throat size is controlled by pore type and that pore size is controlled primarily by facies. When compared with
each other, a pore size range can be estimated if the pore type and the median pore-throat
aperture are known.
Capillary pressure data was also used to understand the behavior of the
dependent rock properties (porosity, permeability, and wettability), and it was
determined that size-reduced samples, regardless of facies, tend to show similar
dependent rock property behavior, but size-enhanced samples show dispersion. Finally,
capillary pressure data was used to understand fluid flow behavior of pore types and
facies. Oncolitic grainstone samples show unpredictable fluid flow behavior compared
to oolitic grainstone samples, yet oncolitic grainstone samples will move a higher
percentage of fluid. Size-enhanced samples showed heterogeneous fluid flow behavior
while the size-reduced samples could be grouped by the number of modes of pore-throat
sizes.
Finally, this study utilized petrographic image analysis to determine if 2-
dimensional porosity values could be calculated and compared to porosity values from
3-dimensional porosity techniques. The complex, heterogeneous pore network found in
the Grayson reservoir rocks prevents the use of petrographic image analysis as a porosity
calculation technique.
|
Page generated in 0.0441 seconds