Abstract Porosity and permeability are the most important attributes of reservoir rock. They determine the amount of fluid a rock can contain and the rate at which that fluid can be produced (Dickey, 1986). Porosity is defined as the "property possessed by a rock of containing interstices, without regard to size, shape, or interconnection of openings. It is expressed as the percentage of the total (bulk) volume occupied by the interstices" (API, 1941). Permeability is a measure of the ability of a rock to transmit fluids. A detailed discussion of porosity and permeability and the measurement of these rock properties is the subject of Chapter 11. Accurate porosity values are critical to predrill evaluation of resources in potential reservoirs (potentially recoverable hydrocarbons in undiscovered fields are called resources, not reserves). Once a discovery is made, reservoir rock properties (porosity/permeability) are used to establish pore volume, hydrocarbon pore volume, recoverable reserves, production rates, well spacings, fluid injection rates, etc. The need for accurate estimates of rock properties extends to the whole "life cycle" (discovery, appraisal, planning, development, and management) of a reservoir (Table 1-1). Porosity and permeability data and estimates provide essential input to mathematical reservoir models, used to evaluate both new and mature fields, and to determine the most efficient method of economic development. Porosity and permeability are also key parameters in basin modeling. Such models help in the interpretation of sedimentary, hydrodynamic, geochemical, and tectonic processes which affected a given area over geologic time. Understanding of processes controlling basin formation

Abstract Most reservoir properties, ranging in scale from megascopic to microscopic, can be ultimately traced to environmental variations within deposi-tional systems. Each depositional environment produces sand bodies which display a certain size and shape, and which exhibit a characteristic range in mineral composition, sedimentary structures, and textures. Following deposition, diagenetic processes affecting reservoir quality of siliciclastic rocks normally proceed along different paths that are directly or indirectly related to environmentally-controlled differences in composition and physical characteristics (Figure 4-1). The effect of depositional facies on reservoir quality in siliciclastics is, obviously, most pronounced in relatively shallow reservoirs. In such rocks, reservoir quality (particularly permeability) is generally controlled by lithofacies (Figure 4-2), which are a product of the depositional environment (e.g., Weber, 1980; Clark and Reinson, 1990). As noted by Weber (1980), in many reservoirs, “it is often possible to work out the train of events leading to present rock properties and to relate these properties to the original sedimentologi-cal characteristics.” The influence of depositional facies in not restricted to shallow burial depths. In many (but not all) deeply-buried reservoirs affected by a moderate to heavy diagenetic overprint, the relative quality of each facies does not change significantly (e.g., Weber, 1980; Harms and others, 1981; Lindquist, 1983; Schotchman and Johnes, 1990). As noted by Weber (1980), even in deeply-buried sandstones, “one often finds the same general contrasts in permeability in the reservoir that existed in the original sandstone body but with an enhancement of the ratio between maximum and minimum permeabilities.” Permeability trends

Abstract After two decades of research, secondary porosity remains one of the most controversial topics in clastic sedimentary petrology and reservoir quality assessment. Although the ubiquity of such porosity in sandstones of all ages worldwide is unquestionable, fumdamental disagreements remain as to its practical importance, origin, and effect on reservoir quality prediction. It appears that the significance of secondary porosity and its impact on sandstone reservoir quality is frequently overemphasized. This can be attributed to two factors: the subjective nature of the criteria used in defining and quantifying secondary porosity the erroneous assumption that the presence of secondary porosity automatically results in a net increase of total porosity and permeability A critical review of processes thought to be responsible for secondary proposity generation suggests that meteoric water influx provides the most effective leaching mechanism. Importantly, some of this porposity can be preseved during deeper burial, particularly in sandstones with high percentages of non-ductile grains. Silicate hydrolysis is probably the most important porosity-generating process in the deep subsurface. However, porosity created by this process is mostly “redistributional” (the volume increase produced by dissolution of minerals is counterbalanced by a similar volume decrease generated by precipitation of pore-filling diagenetic phases representing products of the dissolution reactions). The importance of organic acids as a quantitatively important porosity- enhancing medium is not clear. The presence of secondary porosity does not appear to significantly affect the accuracy of empirical predictions in many sandstones for two reasons: The extent of secondary porosity and permeability generation and

Abstract The dependence of sandstone reservoir quality on composition has been recognized in numerous empirical studies (e.g., Hayes and others, 1976; Nagtegaal, 1978; Selley, 1978; Seeman and Scherer, 1984; Scherer, 1987; Smosna, 1989) and in experimental studies (Pittman and Larese, 1991). The composition and relative abundance of detrital components in sands greatly influence both physical and chemical diagenesis and, thus, reservoir quality. The purpose of this chapter is to discuss some of the effects of detrital composition on porosity and permeability and then review evaluation of mineral composition of a potential reservoir prior to drilling.

Abstract Porosity data are an integral part of all databases used to develop predictive models of reservoir quality. In most instances, such data are obtained from core analysis and/or log analysis (discussed in the preceding chapter). However, useful porosity data also can be generated from petrographic point counts. Point counts (modal analyses) provide quantitative data on both total thin-section porosity and specific types of porosity. Four types of porosity occur in sandstones: intergranular, dissolution, micro, and fracture (Pittman, 1978). Intergranular pores can be identified in thin section by their location between detrital grains. Identification of dissolution pores was discussed in detail in the chapter dealing with secondary porosity (Chapter 7). Microporosity is best recognized by using fluorescent microscopy on samples containing fluorescent epoxy injected into the rock's pore system (Yurewicz and Dravis, 1984; Yanguas and Dravis, 1985). Fracture porosity is generally less than 1 to 2% and does not contribute significantly to total porosity. Fracture porosity cannot be estimated reliably from thin sections. Modal analysis of porosity is usually part of a general procedure to quantify the volumes of sandstone elements (grains, cements, and pores). Unlike other techniques, petrographic analysis can also provide information on the processes involved in porosity reduction or enhancement (or both) and thus help in the choice of parameters for predictive equations. Most importantly, petrographic observations provide clues as to the best approach to be used in reservoir quality prediction for a given target population (see Chapters 20 through 22 involving case histories). Other than measurements on unconsolidated

Abstract Two reservoir quality assessment case studies (Kekiktuk Formation sandstones and Yacheng field) have been discussed in preceding chapters (Chapters 4 and 8). The Yacheng reservoir quality prediction model was based on a calibration data set from wells with similar temperature and effective pressure histories. As a result of these similarities, reservoir quality was simply a function of depositionally-controlled differences in composition, sorting, and grain size. In contrast, reservoir quality in the Kekiktuk Formation sandstone was controlled primarily by texture (grain size) and burial history. In this chapter, three more case studies are discussed (Middle Jurassic sandstones of the Fangst group, offshore mid-Norway; Late Cretaceous-Late Eocene sandstones in the Taranaki basin, New Zealand; and Middle Eocene-Late Oligocene sandstones of the San Emigdio area, California). The reservoir quality of compositionally- and texturally-similar sandstones from the Haltenbanken area (offshore mid-Norway) is controlled by their burial history. In sandstones of the Taranaki Basin (New Zealand), the key to successful porosity prediction is understanding burial diagenetic processes and, in particular, proper evaluation of the importance of secondary porosity. Finally, a case study from the southernmost San Joaquin basin illustrates an approach to predicting porosity in sandstones with a wide range of zeolite and clay cement abundances.