Difference between revisions of "Pay determination"
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− | The simplest, yet most useful, method for combining this information is a composite log, which displays the different classes of data in a format in which each data set is readily correlated by depth. From a detailed reservoir profile log, pay zones can be identified and correlated to uncored wells using well log curves that are calibrated to core data. Examples of this type of procedure can be found in Connolly and Reed,<ref name=pt06r19>Connolly, E. T., Reed, P. A., 1983, Full spectrum formation evaluation: Canadian Well Logging Society Journal, v. 12, p. 23–69.</ref> Harris,<ref name=pt06r48>Harris, D. G., 1975, The roles of geology in reservoir simulation studies: Journal Petroleum of Technology, May, p. 625–632.</ref> Hearn et al.,<ref name=pt06r51>Hearn, C. L., Ebanks, W. J. Jr., Tye, R. S., Ranganathan, V. 1984, Geological factors influencing reservoir performance of the Hartzog Draw field: Journal of Petroleum Technology, v. 36, Aug., p. 1335–1344, 10, 2118/12016-PA.</ref> and Hietala and Connolly.<ref name=pt06r53>Hietala, R. W., Connolly, E. T., 1984, Integrated rock-log calibration in the Elmworth field, Alberta, Canada, Part II—well log analysis methods and techniques, in Masters, J. A., ed., Elmworth—Case Study of a Deep Basin Gas Field: AAPG Memoir 38, p. 215–242.</ref> | + | The simplest, yet most useful, method for combining this information is a composite log, which displays the different classes of data in a format in which each data set is readily correlated by depth. From a detailed reservoir profile log, pay zones can be identified and correlated to uncored wells using well log curves that are calibrated to core data. Examples of this type of procedure can be found in Connolly and Reed,<ref name=pt06r19>Connolly, E. T., Reed, P. A., 1983, Full spectrum formation evaluation: Canadian Well Logging Society Journal, v. 12, p. 23–69.</ref> Harris,<ref name=pt06r48>Harris, D. G., 1975, The roles of geology in reservoir simulation studies: Journal Petroleum of Technology, May, p. 625–632.</ref> Hearn et al.,<ref name=pt06r51>Hearn, C. L., Ebanks, W. J. Jr., Tye, R. S., Ranganathan, V. 1984, Geological factors influencing reservoir performance of the Hartzog Draw field: Journal of Petroleum Technology, v. 36, Aug., p. 1335–1344, 10, 2118/12016-PA.</ref> and Hietala and Connolly.<ref name=pt06r53>Hietala, R. W., Connolly, E. T., 1984, [http://archives.datapages.com/data/specpubs/fieldst4/data/a013/a013/0001/0200/0215.htm Integrated rock-log calibration in the Elmworth field, Alberta, Canada, Part II—well log analysis methods and techniques], in Masters, J. A., ed., Elmworth—Case Study of a Deep Basin Gas Field: [http://store.aapg.org/detail.aspx?id=67 AAPG Memoir 38], p. 215–242.</ref> |
− | An important component of effective pay determination is a systematic, sedimentologically based reservoir zonation. This procedure provides a direct method of evaluating the validity and representativeness of core measurements in relation to the actual distribution of porosity, permeability, and fluid saturations within the reservoir. Core description should be integrated with well logs for calibration and correlation to uncored wells. Discussion of calibration techniques can be found in Connolly and Reed,<ref name=pt06r19 /> Hietala and Connolly,<ref name=pt06r53 /> and Sneider and King.<ref name=pt06r128>Sneider, R. M., King, H. R., 1984, Integrated rock-log calibration in the Elmworth field, Alberta, Canada—Part I, Reservoir rock detection and characterization, in Masters, J. A., ed., Elmworth—Case Study of a Deep Basin Gas Field, AAPG Memoir 38, p. 205–214.</ref> | + | An important component of effective pay determination is a systematic, sedimentologically based reservoir zonation. This procedure provides a direct method of evaluating the validity and representativeness of core measurements in relation to the actual distribution of porosity, permeability, and fluid saturations within the reservoir. Core description should be integrated with well logs for calibration and correlation to uncored wells. Discussion of calibration techniques can be found in Connolly and Reed,<ref name=pt06r19 /> Hietala and Connolly,<ref name=pt06r53 /> and Sneider and King.<ref name=pt06r128>Sneider, R. M., King, H. R., 1984, [http://archives.datapages.com/data/specpubs/fieldst4/data/a013/a013/0001/0200/0205.htm Integrated rock-log calibration in the Elmworth field, Alberta, Canada—Part I, Reservoir rock detection and characterization], in Masters, J. A., ed., Elmworth—Case Study of a Deep Basin Gas Field, [http://store.aapg.org/detail.aspx?id=67 AAPG Memoir 38], p. 205–214.</ref> |
Well and production tests are often taken over too large an interval in the wellbore to be precise in distinguishing pay and nonpay, especially in heterogeneous reservoirs. Spinner and temperature surveys can be good indicators of the loci of production where the borehole penetrates the reservoir if production rates are high enough. Electric logs can delineate hydrocarbon saturated intervals, but are not an effective tool for pay determination until they are calibrated with production tests, core analyses, or results from analogous reservoirs. The effective determination of pay relies on analyses from the physical sampling of reservoir and nonreservoir rocks. The different classes of information regarding reservoir behavior and pay determination may be irreconcilable or open to misinterpretation in the absence of a thoroughly understood geological framework. | Well and production tests are often taken over too large an interval in the wellbore to be precise in distinguishing pay and nonpay, especially in heterogeneous reservoirs. Spinner and temperature surveys can be good indicators of the loci of production where the borehole penetrates the reservoir if production rates are high enough. Electric logs can delineate hydrocarbon saturated intervals, but are not an effective tool for pay determination until they are calibrated with production tests, core analyses, or results from analogous reservoirs. The effective determination of pay relies on analyses from the physical sampling of reservoir and nonreservoir rocks. The different classes of information regarding reservoir behavior and pay determination may be irreconcilable or open to misinterpretation in the absence of a thoroughly understood geological framework. |
Revision as of 16:02, 5 February 2014
Development Geology Reference Manual | |
Series | Methods in Exploration |
---|---|
Part | Geological methods |
Chapter | Effective pay determination |
Author | Gerard C. Gaynor, Robert M. Sneider |
Link | Web page |
Store | AAPG Store |
Pay determination is a key component in the calculation of the expected volume of recoverable hydrocarbons from a field under a set of known or predicted economic conditions. It is of importance from the field discovery, through initial appraisal and development phases, to final abandonment. The uncertainties associated with pay determination can be circumscribed only by a thorough integration and interpretation of geological and engineering data.
Pay and nonpay concepts
Pay is defined as that part of a reservoir unit from which hydrocarbons can be produced at economic rates given a specific production method. This concept of pay links the physical characteristics of the reservoir (rock properties, fluid saturations, and capillary behavior) to the economic aspects of production (completion method, recovery techniques, and volumetric estimates of reserves). Nonpay is defined as the part of a reservoir unit that will not produce hydrocarbons at economic rates and includes intrareservoir barriers.
A reservoir rock is any porous and permeable rock capable of potentially containing hydrocarbons in its pore system. This statement implies that not all reservoir rocks qualify as pay. In some reservoirs, there may be intermediate pay types or a continuum between pay and nonpay intervals. This situation may include reservoir units that have differing fluid saturations or pore geometries, or that are present at different elevations above the hydrocarbon-water contact.
The production methodologies—primary, secondary, and enhanced recovery—affect the definition of pay. For example, beds with limited lateral continuity may qualify as pay under primary production, but may not be waterfloodable at contemplated injector-producer well spacings, thus disqualifying them as pay under secondary production. Thus, there are two separate but related questions regarding pay determination: first, the delineation of reservoir quality rock, and second, the classification of that part of a reservoir quality interval as pay.
Pay determination techniques
The steps and information necessary for the effective determination of pay in a reservoir are outlined in Table 1. Data sources include the following:
- Results of sedimentological studies, preferably using conventional cores (see Lithofacies and environmental analysis of clastic depositional systems)
- Core analysis
- Analysis of the capillary system of selected core samples (see Capillary pressure)
- Thin section petrography and electron microscopy for mineral composition and pore geometry (see Reservoir quality) and Thin section analysis and SEM, XRD, CL, and XF Methods
- Well logs, including measures of the lithology, porosity, and fluid saturation
- Production history and well test results, including spinner and temperature surveys
- Ancillary data, including mud logs, drillers' logs, and show evaluations
Step | Procedure |
---|---|
1. Geologically characterize reservoir | Core description, wireline log calibration, lithofacies determination, depositional environment analysis |
2. Determine reservoir properties | Core analysis (porosity, permeability, fluid saturation), wireline log analysis (porosity, fluid saturation) |
3. Delineate reservoir and nonreservoir rocks and characterize pore space geometry | Porosity/permeability crossplots, thin section petrography, pore cast electron microscopy, mercury injection capillary analysis; apply cut-off criteria (Table 2) |
4. Evaluate pay and nonpay | Mercury injection capillary analysis, fluid saturation analysis; apply cut-off criteria (Table 3) |
5. Confirm pay zones | Measure well performance using spinner, temperature, flowmeter data and production results; observations noted during drilling, including shows |
The simplest, yet most useful, method for combining this information is a composite log, which displays the different classes of data in a format in which each data set is readily correlated by depth. From a detailed reservoir profile log, pay zones can be identified and correlated to uncored wells using well log curves that are calibrated to core data. Examples of this type of procedure can be found in Connolly and Reed,[1] Harris,[2] Hearn et al.,[3] and Hietala and Connolly.[4]
An important component of effective pay determination is a systematic, sedimentologically based reservoir zonation. This procedure provides a direct method of evaluating the validity and representativeness of core measurements in relation to the actual distribution of porosity, permeability, and fluid saturations within the reservoir. Core description should be integrated with well logs for calibration and correlation to uncored wells. Discussion of calibration techniques can be found in Connolly and Reed,[1] Hietala and Connolly,[4] and Sneider and King.[5]
Well and production tests are often taken over too large an interval in the wellbore to be precise in distinguishing pay and nonpay, especially in heterogeneous reservoirs. Spinner and temperature surveys can be good indicators of the loci of production where the borehole penetrates the reservoir if production rates are high enough. Electric logs can delineate hydrocarbon saturated intervals, but are not an effective tool for pay determination until they are calibrated with production tests, core analyses, or results from analogous reservoirs. The effective determination of pay relies on analyses from the physical sampling of reservoir and nonreservoir rocks. The different classes of information regarding reservoir behavior and pay determination may be irreconcilable or open to misinterpretation in the absence of a thoroughly understood geological framework.
Of all the methods available for the prediction of the behavior of the rock-fluid system, capillary analysis is essential in determining pay because the displacement characteristics of hydrocarbons are dependent on pore throat geometries, fluid saturations, and the respective fluid properties of immiscible wetting and nonwetting phases,
Methods of capillary pressure analysis (such as mercury injection) and the interpretation of capillary behavior in reservoir rocks can be found in Wardlaw and Taylor.[6] Mercury injection capillary pressure curves can be readily transformed for predicting fluid behavior during production, locating transition zones, and estimating water cut during production.
The initial delineation of reservoir quality rocks can be obtained by crossplotting such quantities as porosity, permeability, and fluid saturation in which these attributes are identified by lithofacies, depositional environment, or any other valid geologically based description that zones the reservoir into genetically distinct units. Hydrocarbon fluid saturation within the rock pore space is not a factor in determining reservoir rock qualify. A set of guidelines that identifies reservoir quality and nonreservoir rocks in most cases is shown in Table 2. These criteria have been derived from monitoring the production history of different rock types in varied geological settings in hundreds of wells. A relative ranking system of reservoir and nonreservoir rock types can be established using this table in cases where some, but not all, criteria are met.
Criterion | Reservoir | Nonreservoir |
---|---|---|
Initial displacement pressure (psi) | >100 | |
Capillary pressure (psi) (1% bulk volume Hg fluid saturation) | >500 | |
Bulk volume Hg fluid saturation at 1000 psi | >3% | |
Bulk volume Hg fluid saturation at 2000 psi | >>3% | |
Distribution of effective pore throat radii at 2000 psi capillary pressure | >50% of radii ≥ 0.05 μm | >50% of radii ≤ 0.05 μm |
The location of reservoir quality rocks and their relative rankings should be added to the reservoir profile log. After reservoir quality rock has been identified, the initial determination of pay within the reservoir can be made on the basis of cut-off values shown in Table 3. These cut-off values should be applied absolutely only in the context of a geologically based characterization of the reservoir and never presumptively.
Classification | Bulk Volume(%) | Pore Volume (%) |
---|---|---|
Pay | >4 | >40 |
~3–4 | >30–40 | |
Intermediate | ~2–3 | >22–30 |
Nonpay | >1–2 | >10–22 |
≥1 | ≥10 |
Pay determined by the foregoing procedure should be confirmed under a specific production method. The final step should be to correlate well and production tests, injection or production profiles, and any show or other information obtained during drilling to locate producing zones accurately. These zones should be compared with the expected pay as determined in the outlined procedure and the reasons for similarities and differences fully investigated and explained. Pay criteria specific to the field situation can then be refined. Uncertainties (and there always will be these) regarding the reservoir can be circumscribed and addressed using other investigative tools, such as field-scale tracer studies or wettability studies of the separate phases. The procedure allows the differentiation of classes of pay that may relate to primary, secondary, or enhanced recovery phases of field development or equity allocations.
The determination of pay is an estimate and is only as good as the data and its interpretation. A clear and obvious implication is that reliance on a single data source for pay determination, such as electric logs or well test results, is neither appropriate nor advisable. As new information, such as a relatively long-term production history, becomes available, pay delineation should be reevaluated.
See also
- Introduction to geological methods
- Subsurface maps
- Conversion of well log data to subsurface stratigraphic and structural information
- Correlation and regression analysis
- Reservoir quality
- Fluid contacts
References
- ↑ 1.0 1.1 Connolly, E. T., Reed, P. A., 1983, Full spectrum formation evaluation: Canadian Well Logging Society Journal, v. 12, p. 23–69.
- ↑ Harris, D. G., 1975, The roles of geology in reservoir simulation studies: Journal Petroleum of Technology, May, p. 625–632.
- ↑ Hearn, C. L., Ebanks, W. J. Jr., Tye, R. S., Ranganathan, V. 1984, Geological factors influencing reservoir performance of the Hartzog Draw field: Journal of Petroleum Technology, v. 36, Aug., p. 1335–1344, 10, 2118/12016-PA.
- ↑ 4.0 4.1 Hietala, R. W., Connolly, E. T., 1984, Integrated rock-log calibration in the Elmworth field, Alberta, Canada, Part II—well log analysis methods and techniques, in Masters, J. A., ed., Elmworth—Case Study of a Deep Basin Gas Field: AAPG Memoir 38, p. 215–242.
- ↑ Sneider, R. M., King, H. R., 1984, Integrated rock-log calibration in the Elmworth field, Alberta, Canada—Part I, Reservoir rock detection and characterization, in Masters, J. A., ed., Elmworth—Case Study of a Deep Basin Gas Field, AAPG Memoir 38, p. 205–214.
- ↑ Wardlaw, N. C., 1976, Pore geometry of carbonate rocks as revealed by pore casts and capillary pressure: AAPG Bulletin, v. 60, p. 245–257.