Changes

|   Dolomite

|   Dolomite

| Oregon basin Field, Wyoming

| Oregon basin Field, Wyoming

| <ref name=pt06r91>Morgan, J. T., Cordiner, F. S., Livingston, A. R., 1977, Tensleep reservoir study, Oregon Basin field, Wyoming— reservoir characteristics: Journal of Petroleum Technology, v. 29, p. 886–896., 10., 2118/6141-PA</ref>

| <ref name=pt06r91>Morgan, J. T., Cordiner, F. S., Livingston, A. R., 1977, Tensleep reservoir study, Oregon Basin field, Wyoming— reservoir characteristics: Journal of Petroleum Technology, v. 29, p. 886–896, DOI: [https://www.onepetro.org/journal-paper/SPE-6141-PA 10.2118/6141-PA].</ref>

|-

|-

|   Anhydrite

|   Anhydrite

|   Authigenic clays

|   Authigenic clays

| Hankensbuttel-Sud Field, Germany

| Hankensbuttel-Sud Field, Germany

| <ref name=pt06r34>Gaida, K. H., Kessel, D. G., Volz, H., Zimmerle, W. 1987, Geologic parameters of reservoir sandstones as applied to [[enhanced oil recovery]]: SPE Formation Evaluation, v. 2, p. 89–96., 10., 2118/13570-PA</ref>

| <ref name=pt06r34>Gaida, K. H., Kessel, D. G., Volz, H., Zimmerle, W. 1987, Geologic parameters of reservoir sandstones as applied to [[enhanced oil recovery]]: SPE Formation Evaluation, v. 2, p. 89–96, DOI: [https://www.onepetro.org/journal-paper/SPE-13570-PA 10.2118/13570-PA].</ref>

|-

|-

| Stylolitization and associated cementation

| Stylolitization and associated cementation

| Faulting/fracturing

| Faulting/fracturing

| Anschutz Ranch Field, Wyoming

| Anschutz Ranch Field, Wyoming

| <ref name=pt06r77>Lindquist, S. J., 1983, Nugget Formation reservoir characteristics affecting production the Overthrust Belt of southwestern Wyoming: Journal of Petroleum Technology, July, p. 1355–1365.</ref>

| <ref name=pt06r77>Lindquist, S. J., 1983, [https://www.onepetro.org/journal-paper/SPE-10993-PA Nugget Formation reservoir characteristics affecting production the Overthrust Belt of southwestern Wyoming]: Journal of Petroleum Technology, July, p. 1355–1365.</ref>

|}

|}

===Step 1. Basic rock description===

===Step 1. Basic rock description===

The geologist first collects data relating to the relative abundance of diagenetic components recognizable at the magnification levels of a binocular microscope or handlens. This evaluation may be conducted simultaneously with the rock description step of depositional model construction. The most useful data are derived from slabbed full diameter cores, but recourse to cuttings and sidewall cores is necessary where such cores are not available. In addition to describing the slabbed core, horizontal core plugs used for core analysis measurements should also be described. Recent advances in the methodology of cuttings analysis involve visual aids such as cuttings comparators, low magnification (20&times;) photographs of cuttings samples, thin section photomicrographs, and scanning electron microscope (SEM) micrographs of rock chips and pore casts. These allow more extensive utilization of these samples for rock characterization.<ref name=pt06r131>Sneider, R. M., King, H. R., Hawkes, H. E., Davis, T. B., 1983, Methods for detection and characterization of reservoir rock, Deep Basin gas area, western Canada: Journal of Petroleum Technology, Sept., p. 1725–1734.</ref>

The geologist first collects data relating to the relative abundance of diagenetic components recognizable at the magnification levels of a binocular microscope or handlens. This evaluation may be conducted simultaneously with the rock description step of depositional model construction. The most useful data are derived from slabbed full diameter cores, but recourse to cuttings and sidewall cores is necessary where such cores are not available. In addition to describing the slabbed core, horizontal core plugs used for core analysis measurements should also be described. Recent advances in the methodology of cuttings analysis involve visual aids such as cuttings comparators, low magnification (20&times;) photographs of cuttings samples, thin section photomicrographs, and scanning electron microscope (SEM) micrographs of rock chips and pore casts. These allow more extensive utilization of these samples for rock characterization.<ref name=pt06r131>Sneider, R. M., King, H. R., Hawkes, H. E., Davis, T. B., 1983, [https://www.onepetro.org/journal-paper/SPE-10072-PA Methods for detection and characterization of reservoir rock, Deep Basin gas area, western Canada]: Journal of Petroleum Technology, Sept., p. 1725–1734.</ref>

===Step 2. Quantitative analysis===

===Step 2. Quantitative analysis===

The basic correlation techniques in common use include marker and sequence analysis and, where continuity is very limited, slice techniques.<ref name=pt06r18>Cant, D. J., 1984, Subsurface facies analysis, in Walker, R. G., ed., Facies Models: Geoscience Canada, Reprint Series 1, p. 297–319.</ref> Correlation of diagenetic zones is most accurate when the origins and timings of the diagenetic events creating the components of interest are well understood, the sample and well spacing are relatively small, the diagenetic zones are relatively thick, and the sequence of zones is unique.

The basic correlation techniques in common use include marker and sequence analysis and, where continuity is very limited, slice techniques.<ref name=pt06r18>Cant, D. J., 1984, Subsurface facies analysis, in Walker, R. G., ed., Facies Models: Geoscience Canada, Reprint Series 1, p. 297–319.</ref> Correlation of diagenetic zones is most accurate when the origins and timings of the diagenetic events creating the components of interest are well understood, the sample and well spacing are relatively small, the diagenetic zones are relatively thick, and the sequence of zones is unique.

The distribution of reservoir fluids or pressures at the time of discovery of the reservoir, or at subsequent intervals during field development, may indicate the presence of continuous permeability barriers and thus may help to confirm the extent of some diagenetic zones. When the basic correlation techniques prove unsatisfactory or inadequate due to a high degree of complexity or low degree of confidence, the geologist may need to resort to special engineering techniques such as pulse testing <ref name=Pierce_1977>Pierce, A. E., 1977, Case history: Waterflood performance predicted by pulse testing, Journal of Petroleum Technology, v. 29, p. 914-918.</ref> or tracer studies <ref name=Wagner_1977>Wagner, O. R., 1977, The use of tracers in diagnosing interwell reservoir heterogeneities: Field results, Journal of Petroleum Technology, v. 29, p. 1410-1416.</ref> (Table 4), or to probabilistic modeling <ref name=Hewett and Behrens_1988>Hewett, T. A., and R. A. Behrens, 1988, Conditional simulation of reservoir heterogeneity with fractals, 63rd Annual SPE Technical Conference Proceedings, p. 645-660, SPE #18326.</ref> (see [[Integrated computer methods]]).

The distribution of reservoir fluids or pressures at the time of discovery of the reservoir, or at subsequent intervals during field development, may indicate the presence of continuous permeability barriers and thus may help to confirm the extent of some diagenetic zones. When the basic correlation techniques prove unsatisfactory or inadequate due to a high degree of complexity or low degree of confidence, the geologist may need to resort to special engineering techniques such as pulse testing <ref name=Pierce_1977>Pierce, A. E., 1977, [https://www.onepetro.org/journal-paper/SPE-6196-PA Case history: Waterflood performance predicted by pulse testing], Journal of Petroleum Technology, v. 29, p. 914-918.</ref> or tracer studies <ref name=Wagner_1977>Wagner, O. R., 1977, [https://www.onepetro.org/journal-paper/SPE-6046-PA The use of tracers in diagnosing interwell reservoir heterogeneities: Field results], Journal of Petroleum Technology, v. 29, p. 1410-1416.</ref> (Table 4), or to probabilistic modeling <ref name=Hewett and Behrens_1988>Hewett, T. A., and R. A. Behrens, 1988, [https://www.onepetro.org/journal-paper/SPE-18326-PA Conditional simulation of reservoir heterogeneity with fractals], 63rd Annual SPE Technical Conference Proceedings, p. 645-660, SPE #18326.</ref> (see [[Integrated computer methods]]).

{| class = "wikitable"

{| class = "wikitable"

In this stage, it is necessary for the geologist to subdivide each well (reservoir quality profile) into relatively homogeneous units or zones. Initially it is best to construct a relatively detailed zonation reflecting major variations in reservoir rock characteristics regardless of their vertical dimensions ([[:file:evaluating-diagenetically-complex-reservoirs_fig4.png|Figure 4]]).

In this stage, it is necessary for the geologist to subdivide each well (reservoir quality profile) into relatively homogeneous units or zones. Initially it is best to construct a relatively detailed zonation reflecting major variations in reservoir rock characteristics regardless of their vertical dimensions ([[:file:evaluating-diagenetically-complex-reservoirs_fig4.png|Figure 4]]).

Zonation may be facilitated by establishing criteria by which major categories of reservoir rock types present can be distinguished. Semilog crossplots of porosity and permeability keyed to texture, matrix content, and diagenetic component content are very useful. Through examination of these plots, the geologist can quickly separate samples into natural groupings ([[:file:evaluating-diagenetically-complex-reservoirs_fig3.png|Figure 3]]). Because permeability directly reflects fluid flow capacity, it is the major parameter used to designate reservoir rock categories. Because porosity is commonly a major control on permeability, it generally exhibits a positive correlation with that variable. Attempts to create hierarchies of permeability heterogeneity based strictly on depositional criteria<ref name=Lewis_1988>Lewis, J. J. M., 1988, Outcrop-derived quantitative models of permeability heterogeneity for genetically different sand bodies: 63rd Annual SPE Technical Conference Proceedings, p.449-463, SPE #18153</ref>  should be avoided in reservoirs where diagenetic alterations are major controls on permeability heterogeneity. If natural groupings are not present, it may be necessary to set arbitrary group boundaries, such as porosity or permeability cutoffs.

Zonation may be facilitated by establishing criteria by which major categories of reservoir rock types present can be distinguished. Semilog crossplots of porosity and permeability keyed to texture, matrix content, and diagenetic component content are very useful. Through examination of these plots, the geologist can quickly separate samples into natural groupings ([[:file:evaluating-diagenetically-complex-reservoirs_fig3.png|Figure 3]]). Because permeability directly reflects fluid flow capacity, it is the major parameter used to designate reservoir rock categories. Because porosity is commonly a major control on permeability, it generally exhibits a positive correlation with that variable. Attempts to create hierarchies of permeability heterogeneity based strictly on depositional criteria<ref name=Lewis_1988>Lewis, J. J. M., 1988, [https://www.onepetro.org/conference-paper/SPE-18153-MS Outcrop-derived quantitative models of permeability heterogeneity for genetically different sand bodies]: 63rd Annual SPE Technical Conference Proceedings, p.449-463, SPE #18153</ref>  should be avoided in reservoirs where diagenetic alterations are major controls on permeability heterogeneity. If natural groupings are not present, it may be necessary to set arbitrary group boundaries, such as porosity or permeability cutoffs.

Estimation of the lateral distribution of zones is then guided by relationships developed in the integrated geological model and documented in the form of maps and cross sections.

Estimation of the lateral distribution of zones is then guided by relationships developed in the integrated geological model and documented in the form of maps and cross sections.

===Stage 7. Model testing and revision===

===Stage 7. Model testing and revision===

Where economics dictate, it may be necessary to test the accuracy of the models developed. This can include testing by history matching of pressures, production rates, and GOR values for segments of the model or full scale testing of the complete model<ref name=pt06r155>Weber, K. J., Klootwijk, P. H., Knoieczek, J., van der Vlugt, W. R., 1978, Simulation of water injection in a barrier-bar- type, oil-rim reservoir in Nigeria: Journal of Petroleum Technology, v. 30, p. 1555–1565., 10., 2118/6702-PA</ref> (see [[Product histories]] and [[Conducting a reservoir simulation study: an overview]]). Testing can also involve drilling additional wells, conducting special engineering tests (pulse or tracer), and collecting geological data on additional samples. Revisions may also be required as additional wells, particularly infill wells, are drilled in the field.

Where economics dictate, it may be necessary to test the accuracy of the models developed. This can include testing by history matching of pressures, production rates, and GOR values for segments of the model or full scale testing of the complete model<ref name=pt06r155>Weber, K. J., Klootwijk, P. H., Knoieczek, J., van der Vlugt, W. R., 1978, Simulation of water injection in a barrier-bar- type, oil-rim reservoir in Nigeria: Journal of Petroleum Technology, v. 30, p. 1555–1565, DOI: [https://www.onepetro.org/journal-paper/SPE-6702-PA 10.2118/6702-PA].</ref> (see [[Product histories]] and [[Conducting a reservoir simulation study: an overview]]). Testing can also involve drilling additional wells, conducting special engineering tests (pulse or tracer), and collecting geological data on additional samples. Revisions may also be required as additional wells, particularly infill wells, are drilled in the field.

==See also==

==See also==