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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, 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>

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, 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>

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.

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,

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<ref name=pt06r149>Wardlaw, N. C., 1976, Pore geometry of carbonate rocks as revealed by pore casts and capillary pressure: AAPG Bulletin, v. 60, p. 245–257.</ref>. Mercury injection capillary pressure curves can be readily transformed for predicting fluid behavior during production, locating transition zones, and estimating water cut during production.

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.<ref name=pt06r149>Wardlaw, N. C., 1976, Pore geometry of carbonate rocks as revealed by pore casts and capillary pressure: AAPG Bulletin, v. 60, p. 245–257.</ref> 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.

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.