--> --> Predicting Sandstone Reservoir System Quality and Example of Petrophysical Evaluation; Dan J. Hartmann, Edward A. Beaumont, and Edward Coalson; Search and Discovery Article #40005 (2000)
[First Hit]

Datapages, Inc.Print this page

Predicting Previous HitSandstoneNext Hit Reservoir System Quality and Example of Petrophysical Evaluation*

Dan J. Hartmann, Edward A. Beaumont, and Edward Coalson

Search and Discovery Article #40005 (2000)

*Adaptation and revision for online presentation of part of Chapter 9, Predicting Reservoir System Quality and Performance, by Dan J. Hartmann and Edward A. Beaumont, in Exploring for Oil and Gas Traps, Edward A. Beaumont and Norman H. Foster, eds., Treatise of Petroleum Geology, Handbook of Petroleum Geology, 1999.

 

Contents

List of Figures

List of Tables

Overview

Introduction

Sandstones vs. Carbonates

Predicting Previous HitSandstoneNext Hit Porosity and Previous HitPermeabilityNext Hit

     General Statement

     Previous HitSandstoneNext Hit Diagenetic Processes

     Effect of Composition and Texture on Previous HitSandstoneNext Hit Diagenesis

     Hydrology and Previous HitSandstoneNext Hit Diagenesis

     Influence of Depositional Environment on Previous HitSandstoneNext Hit Diagenesis

     Predicting Previous HitSandstoneNext Hit Reservoir Porosity

     Predicting Previous HitSandstoneNext Hit Previous HitPermeabilityNext Hit Previous HitfromNext Hit Texture

      Estimating Previous HitSandstoneNext Hit Previous HitPermeabilityNext Hit Previous HitfromNext Hit Previous HitCuttingsNext Hit

Example of Petrophysical Evaluation: Evaluation of Saturation Profiles

     General Statement

     Setting and Structure of the Sorrento Field

     Morrow Lithofacies and Pore Types

      Sorrento Water Saturation Calculations

      Petrophysical Analysis of Sorrento Field Wells

     Water Saturation Profile for Sorrento Field

Annotated References

 

List of Figures

Figure 1.  Porosity-depth plot for sandstones Previous HitfromNext Hit two wells with different geothermal gradients. Previous HitFromNext Hit Wilson, 1994a; courtesy SEPM.

 

 

 

 

Figure 2. Effects of sediment composition on mechanical stability and chemical stability. Previous HitFromNext Hit Loucks et al., 1984; courtesy AAPG.

 

 

Figure 3. Water movement processes—meteroic, compactional, and thermobaric. After Galloway, 1984, and Harrison and Tempel, 1993; courtesy AAPG.

 

 

Figure 4. Eh-pH diagram, showing the approximate distribution of various types of subsurface fluids. Previous HitFromNext Hit Shelley, 1985; courtesy W.H. Freeman and Co.

 

 

 

 

Figure 5.  General trend of increasing dissolved solids in subsurface fluids with increasing depth Previous HitFromNext Hit Shelley 1985; courtesy W.H. Freeman and Co.

 

 

 

 

Figure 6.  Factors controlling Previous HitsandstoneNext Hit diagenesis. Previous HitFromNext Hit Stonecipher et al., 1984; courtesy AAPG.

 

Figure 7. Typical diagenetic pathways for marine sediments. After Stonecipher et al., 1984; courtesy AAPG.

 

Figure 8.  Typical diagenetic pathways for warm and wet nonmarine sediments. Previous HitFromNext Hit Burley et al., 1985; courtesy Blackwell Scientific.

 

Figure 9.  Porosity-depth plot of various formations in U.S. Gulf Coast region. Previous HitFromNext Hit Loucks et al., 1984; courtesy AAPG.

 

 

 

 

 

Figure 10.  Provenance controls on porosity evolution. Previous HitFromNext Hit Surdam et al., 1989; courtesy RMAG.

 

 

 

 

 

Figure 11. Effects of near-surface diagenesis on Previous HitsandstoneNext Hit porosity. Previous HitFromNext Hit Surdam et al., 1989; courtesy RMAG.

 

 

 

 

Figure 12.  Effects of mechanical diagenesis on Previous HitsandstoneNext Hit porosity. Previous HitFromNext Hit Surdam et al., 1989; courtesy RMAG.

 

 

 

 

Figure 13.  Diagenetic and burial history for Brent Group sandstones. Previous HitFromNext Hit Wilson, 1994b; courtesy SEPM.

 

 

Figure 14.  Use of burial history in predicting Previous HitsandstoneNext Hit porosity. Previous HitFromNext Hit Hayes, 1983; courtesy AAPG.

 

 

Figure 15.  Effect of grain size on Previous HitpermeabilityNext Hit and porosity. Previous HitFromNext Hit Coalson et al., 1990.

 

 

 

 

 

Figure 16.  Porosity-Previous HitpermeabilityNext Hit relationships for kaolinite-, chlorite-, and illite-emented sandstones. Previous HitFromNext Hit North, 1985; courtesy Allen & Unwin.

 

 

 

 

Figure 17.  Types of clay-mineral occurrences and pore geometry.After Neasham, 1977; courtesy SPE.

 

Figure 18.  Types of detrital clay in Previous HitsandstoneNext Hit. After Wilson and Pittman, 1977; courtesy Journal of Sedimentary Petrology.

 

 

Figure 19. SEM photographs of pore types IA, IB, IC, ID in sandstones. Previous HitFromNext Hit Sneider and King, 1984; courtesy AAPG.

 

 

Figure 20.  SEM photographs of pore types II and III in sandstones. Previous HitFromNext Hit Sneider and King, 1984; courtesy AAPG.

 

 

Figure 21.  Location map of Sorrento Field; structure on base of the Pennsylvanian. Previous HitFromNext Hit Sonnenberg, 1985; courtesy RMAG.

 

 

Figure 22. Structure map with outline of valley fill. Modified Previous HitfromNext Hit Sonnenberg, 1985; courtesy RMAG.

 

 

Figure 23. Ka/F cross plot for well 11 (Figure 22). Previous HitFromNext Hit Hartmann and Coalson, 1990; courtesy RMAG.

 

 

 

 

Figure 24.  Family of capillary-pressure curves. Previous HitFromNext Hit Hartmann and Coalson, 1990; courtesy RMAG.

 

 

 

Figure 25.  Pickett plot for data Previous HitfromNext Hit well 11 (Figure 22). Previous HitFromNext Hit Hartmann and Coalson, 1990; courtesy RMAG.

 

 

Figure 26.  Petrophysical data for well 11 (Figure 22). Previous HitFromNext Hit Hartmann and Coalson, 1990; courtesy RMAG.

 

 

Figure 27.  Bulk-volume-water (Buckles) plot for well 11 (Figure 22). Previous HitFromNext Hit Hartmann and Coalson, 1990; courtesy RMAG.

 

 

Figure 28.  Petrophysical characteristics of well 4 (Figure 22). Previous HitFromNext Hit Hartmann and Coalson, 1990; courtesy RMAG.

 

 

Figure 29. Petrophysical characteristics of well 8 (Figure 22). Previous HitFromNext Hit Hartmann and Coalson, 1990; courtesy RMAG.

 

 

Figure 30. Petrophysical characteristics of well 1 (Figure 22). Previous HitFromNext Hit Hartmann and Coalson, 1990; courtesy RMAG.

 

 

Figure 31. Sw-elevation plot for wells 4, 8, 11 (Figure 22). Previous HitFromNext Hit Hartmann and Coalson, 1990; courtesy RMAG.

 

Back to Contents

List of tables

Table 1.  Comparison of variables affecting reservoir quality in sandstones and carbonates. After Choquette and Pray (1970).

Table 2.  Major diagenetic processes and their impact on porosity. Previous HitFromNext Hit Surdam et al. (1989).

Table 3.  Cements in sandtones, associated water chemistry, and derivation.

Table 4.  Cements vs. facies/environments.

Table 5.  Range in values of parameters Scherer (1987) used in his analysis of Previous HitsandstoneNext Hit reservoirs.

Table 6.  Characteristics of pore types I, II, and III.

Back to Contents

 

Overview

The economic success of any prospect ultimately depends on reservoir system performance. The reservoir system controls two critical economic elements of a prospect: (1) the rate and (2) the amount of hydrocarbons recovered. In geologic terms, pore type and pore-fluid interaction are the most important elements determining reservoir system performance. Understanding how reservoir systems behave on a petrophysical basis helps us predict reservoir system behavior in wildcat situations.

 

Introduction

The interrelationship of reservoir porosity, Previous HitpermeabilityNext Hit, thickness, and lateral distribution determines reservoir system quality. Although quality prediction is most effective with large amounts of superior data, useful predictions can still be made Previous HitfromNext Hit very limited data. This article discusses methods for predicting the quality of Previous HitsandstoneNext Hit reservoir systems.

 

Sandstones vs. Carbonates

Sandstones and carbonates are the dominant reservoir rocks. Although quite similar, they are different. Table 1 (after Choquette and Pray, 1970) compares variables affecting reservoir system quality for sandstones vs. carbonates.

Back to Contents

 

Predicting Previous HitSandstoneNext Hit Porosity and Previous HitPermeabilityNext Hit

 

General Statement

An effective method of predicting Previous HitsandstoneNext Hit reservoir system porosity and Previous HitpermeabilityNext Hit is (1) to predict Previous HitsandstoneNext Hit porosity and Previous HitpermeabilityNext Hit at deposition and then (2) to predict the probable changes to porosity and Previous HitpermeabilityNext Hit as the Previous HitsandstoneNext Hit was buried. Since other texts (Barwis et al., 1989; Galloway and Hobday, 1983) cover the impact of depositional environment on porosity and Previous HitpermeabilityNext Hit, this subsection concentrates on predicting porosity and Previous HitpermeabilityNext Hit by considering the effects of diagenesis.

This section contains the following topics:

  • Previous HitSandstoneNext Hit Diagenetic Processes        

  • Effect of Composition and Texture on Previous HitSandstoneNext Hit Diagenesis       

  • Hydrology and Previous HitSandstoneNext Hit Diagenesis       

  • Influence of Depositional Environment on Previous HitSandstoneNext Hit Diagenesis       

  • Predicting Previous HitSandstoneNext Hit Reservoir Porosity           

  • Predicting Previous HitSandstoneNext Hit Previous HitPermeabilityNext Hit Previous HitfromNext Hit Texture

  • Estimating Previous HitSandstoneNext Hit Previous HitPermeabilityNext Hit Previous HitfromNext Hit Previous HitCuttingsNext Hit

 

Previous HitSandstoneNext Hit Diagenetic Processes

Diagenesis alters the original pore type and geometry of a Previous HitsandstoneNext Hit and therefore controls its ultimate porosity and Previous HitpermeabilityNext Hit. Early diagenetic patterns correlate with environment of deposition and sediment composition. Later diagenetic patterns cross facies boundaries and depend on regional fluid migration patterns (Stonecipher and May, 1992). Effectively predicting Previous HitsandstoneNext Hit quality depends on predicting diagenetic history as a product of depositional environments, sediment composition, and fluid migration patterns.

 

Diagenetic Processes

Previous HitSandstoneNext Hit diagenesis occurs by three processes:

  1. Cementation

  2. Dissolution (leaching)

  3. Compaction

Cementation destroys pore space; grain leaching creates it. Compaction decreases porosity through grain rearrangement, plastic deformation, pressure solution, and fracturing.

 

Diagenetic Zones

Surdam et al. (1989) define diagenetic zones by subsurface temperatures. Depending on geothermal gradient, depths to these zones can vary. Table 2 summarizes major diagenetic processes and their impact on pore geometry.

 

            Effect of Temperature

Depending on geothermal gradient, the effect of temperature on diagenesis can be significant. Many diagenetic reaction rates double with each 10oC increase (1000 times greater with each 100oC) (Wilson, 1994a). Increasing temperatures increase the solubility of many different minerals, so pore waters become saturated with more ionic species. Either (1) porosity-depth plots of sandstones of the target Previous HitsandstoneNext Hit that are near the prospect area or (2) computer models that incorporate geothermal gradient are probably best for porosity predictions.

Figure 1 is a porosity-depth plot for sandstones Previous HitfromNext Hit two wells with different geothermal gradients. The well with the greater geothermal gradient has correspondingly lower porosities than the well with lower geothermal gradient. At a depth of 7000 ft, there is a 10% porosity difference in the trend lines.

 

Effect of Pressure

The main effect of pressure is compaction. The process of porosity loss with depth of burial is slowed by overpressures. Basing his findings mainly on North Sea sandstones, Scherer (1987) notes sandstones retain approximately 2% porosity for every 1000 psi of overpressure during compaction. He cautions this figure must be used carefully because the influence of pressure on porosity depends on the stage of compaction at which the overpressure developed.

 

Effect of Age

In general, sandstones lose porosity with age. In other words, porosity loss in Previous HitsandstoneNext Hit is a function of time. According to Scherer (1987), a Tertiary Previous HitsandstoneNext Hit with a Trask sorting coefficient of 1.5, a quartz content of 75%, and a burial depth of 3000 m probably has an average porosity of approximately 26%. A Paleozoic Previous HitsandstoneNext Hit with the same sorting, quartz content, and burial depth probably has an average porosity of approximately 13%.

 

Effect of Composition and Texture on Previous HitSandstoneNext Hit Diagenesis

Composition and Diagenesis

Composition affects Previous HitsandstoneNext Hit diagenesis in two ways:

  1. The higher the quartz content, the greater the mechanical stability (less compaction occurs).

  2. The higher the variety of minerals, the lower the chemical stability (more cementation or dissolution occurs).

Sandstones with abundant lithics, feldspars, or chert have less occlusion of porosity by quartz overgrowths and more secondary porosity through dissolution of less stable grains. The ratio of quartz to ductile grains is key to compaction porosity loss.

Back to Contents

 

            Sediment Composition and Provenance

Provenance determines sand grain mineralogy and sediment maturity. Mechanical and chemical weathering affects sand grains during transportation. The final product reflects the origin, amount of reworking, and transport distance.

For example, sandstones derived Previous HitfromNext Hit subduction trench margins are generally mineralogically immature. They often contain terrigenous detritus with abundant volcaniclastics and pelagic material. Sandstones derived Previous HitfromNext Hit the margin of a cratonic basin tend to be mineralogically and texturally mature and contain reworked sedimentary detritus.

Figure 2 summarizes the effects of sediment composition on mechanical stability and chemical stability.

 

            Influence of Grain Size on Porosity and Diagenesis

Sorting and grain size are textural parameters that intuitively might seem to have the same effects on the porosity of a reservoir system Previous HitsandstoneNext Hit. Studies show, however, that porosity is largely independent of grain size for unconsolidated sand of the same sorting (Beard and Weyl, 1973). Size does affect Previous HitpermeabilityNext Hit; the finer the sand, the lower the Previous HitpermeabilityNext Hit. Previous HitPermeabilityNext Hit indirectly affects porosity through diagenesis. Stonecipher et al. (1984) suggest that slow fluid fluxes, resulting Previous HitfromNext Hit low Previous HitpermeabilityNext Hit, promote cementation; rapid fluxes promote leaching. In rapid fluxes, solutes do not remain in pore spaces long enough to build local concentration that promotes precipitation of cement. In slow fluxes, they do. Also, size affects the surface area available for diagenetic reactions: the finer the grain size, the greater the grain surface area for a volume of sediment or rock.

 

Influence of Sorting on Porosity

Sorting and porosity strongly correlate in unconsolidated sandstones (Beard and Weyl, 1973). The better the sorting, the higher the porosity. The initial porosities of wet, unconsolidated sands show a range of 44-28% porosity for well-sorted vs. poorly sorted grains. Well-sorted sands tend to have a higher percentage of quartz than do poorly sorted sands, and they tend to maintain higher porosities during burial than poorly sorted sands. Poorly sorted sands have more clay matrix and nonquartz grains.

Back to Contents

 

Hydrology and Previous HitSandstoneNext Hit Diagenesis

        Type of Water Flushes

Much diagenesis occurs in open chemical systems whose initial chemistry is set at deposition. After that, the chemistry of the system changes as flowing water moves chemical components through pores and causes either leaching or cementation of grains. Diffusion also moves chemicals in and out of rocks, although at significantly lower rates. During deep burial, chemical systems close and diagenesis is primarily by pressure solution and quartz overgrowths (Wilson and Stanton, 1994).

Galloway (1984) lists three types of flow of water in a basin:

  1. Meteoric flow--water infiltrates shallow portions of a basin Previous HitfromNext Hit precipitation or surface waters. Deeper infiltration occurs Previous HitfromNext Hit (a) eustatic sea level changes and/or (b) tectonic elevation of basin margins.

  2. Compactional flow--compaction expels water upward and outward Previous HitfromNext Hit the pores of sediments.

  3. Thermobaric flow--water moves in response to pressure gradients caused by generation of hydrocarbons, release of mineral-bound water, and/or increased heat flow.

Figure 3 shows the water movement processes mentioned above.

 

            Pore-Water Chemistry

Depositional environment and climate control initial pore-water chemistry of a Previous HitsandstoneNext Hit. When the rock is buried below the level of meteoric groundwater influence, pore-water chemistry changes as a result of two things:

  1.  Increasing mineral solubility due to increasing temperatures.

  2. Acidic fluids released by maturing organic-rich shales or organic matter in Previous HitsandstoneNext Hit. Acidic pore water leaches carbonate cement and grains.

            Eh-pH Graph

Figure 4 is an Eh-pH diagram, showing the approximate distribution of various types of subsurface fluids.

 

            Pore-water Chemistry and Cements

Table 3 lists common Previous HitsandstoneNext Hit cements and the water chemistry associated with precipitation.

 

            Subsurface Dissolved Solids

Figure 5 shows the general trend of increasing dissolved solids in subsurface fluids with increasing depth.

Back to Contents

 

Influence of Depositional Environment on Previous HitSandstoneNext Hit Diagenesis

Depositional environment influences many aspects of Previous HitsandstoneNext Hit diagenesis. The flow chart (Figure 6) shows the interrelationship of depositional environment with the many factors controlling Previous HitsandstoneNext Hit diagenesis.

 

Sediment Texture and Composition

Depositional environment affects sediment composition by determining the amount of reworking and sorting by size or hydraulic equivalence. Sediments that have a higher degree of reworking are more mechanically and chemically stable. The energy level of depositional environments affects sorting by size or hydraulic equivalence and consequently produces different detrital mineral suites (Stonecipher and May, 1992).

For example, different facies of the Wilcox Group along the Gulf Coast of Texas have different compositions that are independent of their source area (Stonecipher and May, 1992). Wilcox basal fluvial point bar sands are the coarsest and contain the highest proportion of nondisaggregated lithic fragments. Prodelta sands, deposited in a more distal setting, contain fine quartz, micas, and detrital clays that are products of disaggregation. Reworked sands, such as shoreline or tidal sands, are more quartzose.

 

            Depositional Pore-Water Chemistry

Depositional pore-water chemistry of a Previous HitsandstoneNext Hit is a function of depositional environment. Marine sediments typically have alkaline pore water. Nonmarine sediments have pore water with a variety of chemistries. In nonmarine sediments deposited in conditions that were warm and wet, the pore water is initially either acidic or anoxic and has a high concentration of dissolved mineral species (Burley et al., 1985).

 

            Marine Pore-Water Chemistry

Marine water is slightly alkaline. Little potential for chemical reaction exists between normal marine pore water and the common detrital minerals of sediments deposited in a marine environment. Therefore, diagenesis of marine sandstones results Previous HitfromNext Hit a change in pore-water chemistry during burial or the reaction of less stable sediment with amorphous material (Burley et al., 1985).

 

            Marine Diagenesis

The precipitation of cements in quartzarenites and subarkoses deposited in a marine environment tends to follow a predictable pattern beginning with clay authigenesis associated with quartz and feldspar overgrowths, followed by carbonate precipitation. Clay minerals form first because they precipitate more easily than quartz and feldspar overgrowths, which require more ordered crystal growth. Carbonate cement stops the further diagenesis of aluminosilicate minerals.

Figure 7 summarizes typical diagenetic pathways for marine sediments.

 

            Nonmarine Pore-Water Chemistry and Cements

Nonmarine pore-water chemistry falls into two climatic categories: (1) warm and wet or (2) hot and dry. The chemistry of pore waters formed in warm and wet conditions is usually acidic or anoxic with large concentrations of dissolved mineral species. The interaction of organic material with pore water is a critical factor with these waters. The depositional pore water of sediments deposited in hot and dry conditions is typically slightly alkaline and dilute.

Figure 8 shows typical diagenetic pathways for warm and wet nonmarine sediments.

 

Cements

Table 4, compiled Previous HitfromNext Hit data by Thomas (1983), shows the cements that generally characterize specific depositional environments.

 

            Diagenesis and Depositional Pore Waters

In the Wilcox of the Texas Gulf Coast, certain minerals precipitate as a result of the influence of depositional pore-water chemistry (Stonecipher and May, 1990):

  • Mica-derived kaolinite characterizes fluvial/distributary-channel sands flushed by fresh water.

  • Abundant siderite characterizes splay sands and lake sediments deposited in fresh, anoxic water.

  • Chlorite rims characterize marine sands flushed by saline pore water.

  • Glauconite or pyrite characterizes marine sediments deposited in reducing or mildly reducing conditions.

  • Illite characterizes shoreline sands deposited in the mixing zone where brackish water forms.

  • Chamosite characterizes distributary-mouth-bar sands rapidly deposited in the freshwater-marine water mixing zone.

Back to Contents

Predicting Previous HitSandstoneNext Hit Reservoir Porosity

We might have the impression that abundant data and powerful computer models are necessary for porosity prediction. They help. But even with sparse data, by using a little imagination we can predict ranges of porosity. This section presents different methods of predicting Previous HitsandstoneNext Hit porosity. Choose the method(s) most appropriate to your situation.

 

            Porosity-Depth Plots

A pitfall of using porosity-depth plots for porosity prediction is that regression relationship averages out anomalies and complicates predictions of unusually porous sandstones. Use porosity-depth plots for porosity prediction with caution. If enough porosity data are available to make a meaningful plot, keep the "data cloud" on the plot in order to view the ranges of porosity at different depths. In a frontier exploration setting, the usefulness of porosity-depth plots may be limited if global data sets must be used.

Figure 9 presents an example of regression porosity-depth plots for different formations in U.S. Gulf Coast region. Unfortunately it does not include the raw data, so we cannot see porosity variations within each formation. Formations on the left side of the plot, like the Vicksburg, tend to be quartz cemented. Formations on the right side, like the Frio (areas 4-6), tend to be clay cemented.

 

Equation for Porosity Prediction

Scherer (1987) studied the cores of 428 worldwide sandstones and listed the most important variables for predicting Previous HitsandstoneNext Hit porosity:

  • Percentage of quartz grains

  • Sorting

  • Depth of burial

  • Age

Using regression analysis, he developed the following equation:

Porosity = 18.60 + (4.73 x in quartz) + (17.37/sorting) - (3.8 x depth x 10-3) - (4.65 x in age)

where:

            Porosity          =  percent of bulk volume

            In quartz   =  percent of solid-rock volume

            Sorting             =  Trask sorting coefficient

            Depth               =  meters

            In age               =  millions of years

The equation can be used with a high degree of confidence in uncemented to partly cemented sandstones. But if the reduction of porosity by cement exceeds 2.1% bulk volume, then corrections need to be made based on local Previous HitsandstoneNext Hit quality characteristics. Numbers for percent solid volume quartz and sorting may be difficult to obtain. Use 75% for percent solid volume quartz and 1.5 for sorting when these values are not known.

Table 5 shows numbers that Scherer (1987) developed by his analysis of reservoir sandstones.

 

            Predicting Effects of Diagenesis on Porosity

Previous HitSandstoneNext Hit porosity prediction is a matter of estimating original composition and subsequent diagenesis. Use the steps and action presented below to predict Previous HitsandstoneNext Hit porosity.

Step / Action

  1. Estimate the original composition of the Previous HitsandstoneNext Hit Previous HitfromNext Hit provenance (use Figure 10) and depositional environment.

  2. Estimate the effects of near-surface diagenetic processes (see Figure 11).

  3. Estimate the effects of mechanical diagenetic processes (see Figure 12).

  4. Estimate the effects of intermediate and deep burial diagenesis, especially with respect to the creation of secondary porosity.

  5. Using information collected in steps 1 through 4, predict the final porosity ranges using burial history (next procedure).

 

Predicting Effect of Provenance on Diagenesis

Use Figure 10 to predict the effect of original sediment composition on subsequent diagenesis.

 

            Estimating Effect of Near-Surface Diagenesis

Use Figure 11 to estimate the effects of near-surface diagenesis (depth to point where temperature reaches 80oC).

 

            Predicting Effect of Mechanical Diagenesis

Use Figure 12 to predict the effects of mechanical diagenesis on Previous HitsandstoneNext Hit porosity.

 

            Using Burial History to Predict Porosity

Reconstructing burial history aids Previous HitsandstoneNext Hit porosity prediction. A burial history diagram integrates tectonic and hydrologic history with diagenetic evolution to predict Previous HitsandstoneNext Hit porosity. The steps, with recommended action, given below for predicting porosity Previous HitfromNext Hit burial history and are illustrated in Figure 13.

 

Step / Action

  1. Construct a burial history diagram for the formation of interest in the prospect area.

  2. Plot the tectonic history of the basin in the prospect area along the lower x-axis.

  3. Plot the hydrologic history of the prospect area along the lower x-axis. Use the tectonic history to infer the hydrologic history of the prospect.

  4. Plot the porosity curve by combining concepts of diagenetic processes with burial and hydrologic histories of the prospect.

            Example of Using Burial History

Figure 13 is an example of a diagram showing diagenetic and burial history for the Brent Group sandstones, North Sea. Line thicknesses indicate relative abundance of diagenetic components.

Figure 14 is an example of Previous HitsandstoneNext Hit porosity prediction using burial history.

 

            Analog Porosity

Analog porosity values for different depositional environments can help us predict the porosity of reservoir system rocks when the target formation is unsampled within the basin. Analog values, however, may have wide ranges within facies and subfacies of depositional environments. Therefore, we should use care when applying analog data.

Back to Contents

 

Predicting Previous HitSandstoneNext Hit Previous HitPermeabilityNext Hit Previous HitfromNext Hit Texture

Pore type, pore geometry, and fluid properties are critical factors affecting Previous HitpermeabilityNext Hit. Previous HitSandstoneNext Hit texture directly affects pore type and geometry. Knowing what textures and fluids to expect, as well as what authigenic clays might be present, can help us predict Previous HitpermeabilityNext Hit.

 

            Effects of Pore Type and Geometry

Pore type, defined by pore throat size (i.e., macroporosity), directly controls rock Previous HitpermeabilityNext Hit. Pore throat size limits flow capacity. Pore geometry also affects Previous HitpermeabilityNext Hit, but not as much. The rougher the surface of the pore, the more difficult for fluid to flow through the pore and the lower the Previous HitpermeabilityNext Hit.

 

            Effects of Texture

Previous HitSandstoneNext Hit texture affects Previous HitpermeabilityNext Hit as follows:

  1. Decreasing grain size decreases Previous HitpermeabilityNext Hit.

  2. Increasing grain sorting increases Previous HitpermeabilityNext Hit.

  3. Increasing grain rounding increases Previous HitpermeabilityNext Hit.

Figure 15 shows how grain size affects Previous HitpermeabilityNext Hit and porosity.

 

            Rules of Thumb for Gas vs. Oil

Use the following rules of thumb for Previous HitpermeabilityNext Hit for oil vs. gas reservoirs:

  • At >10 md, the reservoir can produce oil without stimulation.

  • At >1 md, the reservoir can produce gas without stimulation.

  • At 1-10 md, the reservoir probably requires stimulation for oil production.

 

            Effect of Authigenic Clays

Pore-bridging clays, like illite, decrease porosity slightly but can destroy Previous HitsandstoneNext Hit Previous HitpermeabilityNext Hit. Discrete particle clay, like kaolinite, lowers porosity and Previous HitpermeabilityNext Hit only slightly. Figure 16 compares porosity-Previous HitpermeabilityNext Hit relationships for kaolinite-, chlorite-, and illite-cemented sandstones. Note there is no significant change in porosities, but permeabilities range over four orders of magnitude.

 

            Pore Geometry and Clay Minerals

Figure 17 shows pore lining and discrete particle clays that decrease porosity and Previous HitpermeabilityNext Hit only slightly in contrast to pore-bridging clays, which decrease porosity slightly but substantially lower Previous HitpermeabilityNext Hit.

 

            Detrital Clay and Previous HitPermeabilityNext Hit

Detrital clays can be part of Previous HitsandstoneNext Hit matrix or grains. As matrix, detrital clays can obliterate Previous HitpermeabilityNext Hit. Detrital grains of clay are often ductile and can be compacted into pore spaces during burial. The percentage of detrital clay in a rock determines Previous HitpermeabilityNext Hit. Figure 18 shows different types of detrital clays in a Previous HitsandstoneNext Hit.

 

            Effect of Quartz Overgrowths

In general, as quartz cement precipitates, the pore-pore throat size ratio approaches 1 (Hartmann et al., 1985). Throats are reduced less than pore space; therefore, Previous HitpermeabilityNext Hit is affected less than porosity. During cementation, the size of the pore spaces between the pore-filling crystals decreases until it approaches the size of the pore throats. Throats become more tabular or sheet-like. Previous HitSandstoneNext Hit porosity may be quite low (<5%) and still have some Previous HitpermeabilityNext Hit (<10 md) where cemented with quartz.

 

            Effect of Fractures

Fractures enhance the Previous HitpermeabilityNext Hit of any Previous HitsandstoneNext Hit reservoir. Fractures are especially important for improving the Previous HitpermeabilityNext Hit of Previous HitsandstoneNext Hit reservoirs with abundant microporosity or disconnected dissolution porosity.

 

            Predicting Previous HitfromNext Hit Texture and Clay Content

Predicting Previous HitsandstoneNext Hit reservoir Previous HitpermeabilityNext Hit is possible as long as we realize that potential errors may be large. Any process that decreases pore throat size decreases Previous HitpermeabilityNext Hit, so predict accordingly. Use steps, with recommended action below, to help predict Previous HitsandstoneNext Hit reservoir Previous HitpermeabilityNext Hit.

Step / Action

  1. Estimate grain size, sorting, and porosity using the depositional environment. For example, if a reservoir is a beach sand, it should be fine- to medium-grained and well sorted with well-rounded quartz grains.

  2. Apply information Previous HitfromNext Hit Step 1 to the porosity-Previous HitpermeabilityNext Hit-grain size plot  (Figure 15). Use porosity and grain size Previous HitfromNext Hit Previous HitsandstoneNext Hit to estimate the Previous HitpermeabilityNext Hit on the chart.

  3. If the Previous HitsandstoneNext Hit is poorly sorted or is cemented, then discount Previous HitpermeabilityNext Hit downward.

  4. Determine if authigenic clay is present. If so, what kind:  pore lining, discrete particle, or pore throat bridging? Adjust Previous HitpermeabilityNext Hit downward according to clay type present.

  5. Determine if detrital clay is present using depositional environment (i.e., high energy = low clay content). If detrital clay is likely, then expect Previous HitpermeabilityNext Hit to be low.

Back to Contents

 

Estimating Previous HitSandstoneNext Hit Previous HitPermeabilityNext Hit Previous HitfromNext Hit Previous HitCuttingsNext Hit

Sneider and King (1984) developed a Previous HitcuttingsNext Hit-based method of Previous HitpermeabilityNext Hit Previous HitestimationNext Hit. Where Previous HitcuttingsNext Hit are available, Previous HitpermeabilityNext Hit estimates can be made by examining the surfaces of Previous HitcuttingsNext Hit for petrophysical Previous HitpermeabilityNext Hit indicators. Estimates of the Previous HitpermeabilityNext Hit for a particular formation can be extended into areas without data in order to predict Previous HitpermeabilityNext Hit.

 

            Basis

Sneider and others at Shell Oil Company developed a methodology for estimating Previous HitpermeabilityNext Hit Previous HitfromNext Hit Previous HitcuttingsNext Hit by calibrating Previous HitpermeabilityNext Hit measured Previous HitfromNext Hit cores with rock-pore parameters described in Previous HitcuttingsNext Hit. Cores of known Previous HitpermeabilityNext Hit were ground up until chips Previous HitfromNext Hit the core were the size of Previous HitcuttingsNext Hit. By using comparators made Previous HitfromNext Hit core chips, they estimated formation Previous HitpermeabilityNext Hit Previous HitfromNext Hit Previous HitcuttingsNext Hit with surprising accuracy. Although Sneider and King (1984) describe the method for estimating Previous HitsandstoneNext Hit Previous HitpermeabilityNext Hit Previous HitfromNext Hit Previous HitcuttingsNext Hit (presented below), procedures could just as easily be developed to predict Previous HitpermeabilityNext Hit of carbonates Previous HitfromNext Hit Previous HitcuttingsNext Hit.

 

            Petrophysical Description

Previous HitFromNext Hit examination of Previous HitcuttingsNext Hit, Previous HitsandstoneNext Hit Previous HitpermeabilityNext Hit can be predicted using the following petrophysical descriptions:

  • Grain size and sorting

  • Degree of rock consolidation

  • Volume percent of clays

  • Pore sizes and pore interconnections

  • Size and distribution of pore throats

 

            Sneider’s Pore Classification for Clastics

Sneider and King (1984) developed a simple method of classifying pore types Previous HitfromNext Hit Previous HitcuttingsNext Hit. The classification of clastic rock pore types Previous HitfromNext Hit Previous HitcuttingsNext Hit is made by comparing pore types with production tests and log analysis. The pore types are as follows:

Type / Description

  1. Rocks with pores capable of producing gas without natural or artificial fracturing.     

  2. Rocks with pores capable of producing gas with natural or artificial fracturing and/or interbedded with type I rocks.

  3. Rocks too tight to produce at commercial rates even with natural or artificial fracturing.

Table 6 lists the characteristics of pore types I, II, and III.

 

            Examples of Pore Type I

The SEM photographs in Figure 19 are examples of rocks with types IA, IB, IC, and ID. Note the amount and connectivity of pore space of each subclass.

 

            Pore Types II and III

The SEM photographs in Figure 20 are examples of rocks with types II and III. Note the amount and connectivity of pore space of each subclass.

 

            Procedure:  Predicting Previous HitSandstoneNext Hit Previous HitPermeabilityNext Hit

The procedure below, with steps and recommended action, is for predicting the Previous HitpermeabilityNext Hit of sandstones Previous HitfromNext Hit Previous HitcuttingsNext Hit using 20x magnification (Previous HitfromNext Hit Sneider and King, 1984).

Step / Action

  1. Estimate grain size and sorting using standard size-sorting comparators, thin section and SEM photomicrographs, and rock photographs.

  2. Estimate volume percentages using Terry-Chillingar charts made for volume estimates.

  3. Estimate consolidation using the scheme described in the preceding table.

  4. Describe the visible and pinpoint porosity and interconnectedness.

  5. Estimate Previous HitpermeabilityNext Hit Previous HitfromNext Hit rocks on comparators and/or using rock characteristics described in the preceding table. (Comparators can be made or purchased.)

  6. Predict Previous HitpermeabilityNext Hit for the formation in prospective areas where petrophysical characteristics are believed to be similar

Back to Contents

 

Example of Petrophysical Evaluation: Evaluation of Saturation Profiles

General Statement

This section shows how saturation profiles can be used to understand the distribution of water saturations within a field or prospect.

The case study presented here is a summary of a larger study of the Sorrento field, southeast Colorado, by Hartmann and Coalson (1990). This study of cores and logs Previous HitfromNext Hit four field wells shows how multiple oil-water contacts and apparent anomalies in saturation profiles in the Sorrento field were due to multiple flow units Previous HitfromNext Hit two separate reservoirs. The study helps us understand shows and water saturations in wells outside Sorrento and therefore is useful for finding other traps in the same formation.

This section contains the following topics:

  • Setting and Structure of the Sorrento Field    

  • Morrow Lithofacies and Pore Types  

  • Sorrento Water Saturation Calculations

  • Petrophysical Analysis of Sorrento Field Wells   

  • Water Saturation Profile for Sorrento Field

 

Setting and Structure of the Sorrento Field

            Index Map

The Sorrento field is in southeastern Colorado on the north flank of the Las Animas Arch. The map (Figure 21) shows the location of the Sorrento field. Structure is contoured on the base of the Pennsylvanian.

 

            Morrow Structure Map

The Sorrento field reservoir is Pennsylvanian Morrow valley-fill sandstones. As shown in Figure 22, structure contours on a marker bed above  the Morrow Previous HitSandstoneNext Hit reflect the irregular thickness of the Previous HitsandstoneNext Hit body and a small structural nose and closure. The oil column is 70 ft (20 m) and exceeds structural closure. This is a combination structural-stratigraphic trap. Fluvial sandstones lap onto marine shale at the margins of the valley, forming lateral seals.

In Figure 22, circled wells represent Marmaton wells; triangles, Mississippian wells; and large X’s, study wells. The rest of the oil wells produce Previous HitfromNext Hit the Morrow. Each unit in the grid is 1 sq mi.

Back to Contents

 

Morrow Lithofacies and Pore Types

By studying core and log data Previous HitfromNext Hit one well (well 11, see Figure 22), we see a picture of a clastic reservoir with wide heterogeneity in total porosities, pore-throat sizes, and capillary pressures. In addition, the depositional environment of these sandstones (fluvial valley fill and Previous HitsandstoneNext Hit) indicates they probably have limited lateral continuity within the valley-fill complex.

 

            Reservoir Lithologic Description

Morrow sandstones in the Sorrento field are slightly shaly, range in grain size Previous HitfromNext Hit very coarse to fine, and are poorly sorted. As a consequence, pores and pore throats also have wide ranges in size. Hand-sample petrography indicates the dominant porosity is intergranular micro- to megaporosity. Clay crystals create minor intercrystalline microporosity in larger pores. Moldic (cement solution?) porosity also may be present but is minor.

 

            Reservoir Porosity and Previous HitPermeabilityNext Hit

Morrow sandstones in Sorrento field have a wide range in porosity and Previous HitpermeabilityNext Hit. Maximum observed porosity (F) is 20-22%, but more typical values are 10-15%. Air permeabilities (Ka) are as great as 1-2 darcies but more commonly are 200-500 md.

In a Ka/F crossplot for well 11 (Figure 23), dots and polygons represent measured Ka/F values. Curves are the graphical solution of Winland’s r35 equation (Pittman, 1992) and represent equal r35 values (port size).

The crossplot shows a large variation in port size for the samples Previous HitfromNext Hit well 11. Areas between dashed lines group points into beds with similar port size, or flow units.

 

          Extrapolated Capillary Pressure Curves and Pore Types

No capillary pressure measurements were available for this study. They were estimated y plotting r35 values on a semilog crossplot of fluid saturation vs. capillary pressure. A capillary pressure curve for each sample passes through its correlative r35 value. Calculations of r35 for well 11 indicate a large variety of capillary pressures and pore types. Pore types for the Morrow samples Previous HitfromNext Hit this well are mega, macro, and micro.

The numbers on the curves in Figure 24 correspond to the numbers on the Ka/F crossplot on Figure 22. Minimum water saturations (“immobile” water) estimated Previous HitfromNext Hit log calculations let us extrapolate the Pc curves into low Sw ranges.

Back to Contents

 

Sorrento Water Saturation Calculations

            Method

Density logs were the primary source of porosity values. Matrix density appears to be about 2.68 g/cc, based on core-measured grain densities (consistent with the presumed mineralogy of the sandstones). Crossplot porosities were not used to avoid introducing a systematic error in these variably shaly sandstones (Patchett and Coalson, 1982).

            Pickett Plot

Formation-water resistivities and water saturations were estimated Previous HitfromNext Hit Pickett plots. The inferred cementation exponent (m) is 1.8 because of the presence of clays, well-connected solution pores (e.g., James, 1989; Muller and Coalson, 1989), or pyrite (Krystinik, L., personal communication). Formation factors measured on core samples Previous HitfromNext Hit well 1 support this interpretation.

The Pickett in Figure 25 shows data Previous HitfromNext Hit well 11. The number labels represent the flow units Previous HitfromNext Hit Figure 24.

            Saturation Exponents, n

Saturation exponents (n) measured on samples Previous HitfromNext Hit well 1 showed variations that relate to pore geometry. Microporous siltstones displayed n greater than 2, indicating either very tortuous pore systems or incomplete saturation by brine during testing. Saturation exponents were less than 2 in the best porosity type. This implies the reservoir is somewhat shaly. However, n was assumed equal to 2 for log calculations because the lab data were not far Previous HitfromNext Hit that value and because lab measurements of saturation exponents are notoriously difficult.

Back to Contents

 

Petrophysical Analysis of Sorrento Field Wells

            Well 11 Flow Units

Flow units were determined in well 11 by plotting and grouping routine core data. The top and bottom of the Morrow (flow units A and 5) are microporous, low-Previous HitpermeabilityNext Hit sandstones that are wet but too tight to produce. Between these are 30 ft (8.5 m) of meso- to macroporous Previous HitsandstoneNext Hit (flow units 1-4).

All pertinent petrophysical data for well 11 are summarized on Figure 26. Previous HitSandstoneNext Hit descriptors found on porosity logs are as follows:

VF = very fine grained   

C   = coarse grained   

  SLTY = silty

F   = fine grained   

VC  = very coarse grained   

SLT   = siltstone

M  = medium grained   

SHY= shaly   

SH    = shale

Subsea elevation of -1,030 ft (-314 m) is marked in the depth track.

 

            Well 11 Water Saturations

Flow unit 4 is macroporous but wet (Sw = 100%); this indicates an oil-water contact. Flow unit 3 is macroporous and has intermediate water saturation (Sw = 70%). This looks like a transition zone. Flow units 2 and 1 are mesoporous and are at immobile water saturation (Sw = 45%). This is verified by the well testing about 100 bo/d and 300 Mcfg/d (16 m3 oil and 8,500 m3 gas per day) with no water Previous HitfromNext Hit perforations in these flow units and by a bulk-volume-water plot following. This lack of water production is remarkable, considering that the well lies only about 25 ft (7 m) above the free water level.

 Figure 27 is the bulk-volume-water (Buckles) plot for well 11.

 

            Well 4

Well 4 hit the Morrow near the top of the oil column. It had the lowest saturations and best flow rates of all the wells studied, even though it had the thinnest reservoir. This is because it contained rock with large pore throats (r35 up to 50m) that was fully saturated with oil (Sw = 25-30%). The well tested 230 bo/d and 387 Mcfg/d (37 m3 oil and 11,000 m3 gas per day). Initial production was 51 bo/d and 411 Mcfg/d (8 m3 oil and 12,000 m3 gas per day). The difference could be due to a loss of reservoir thickness near the well bore, judging Previous HitfromNext Hit the thinness of the reservoir.

Figure 28 summarizes the petrophysical characteristics of well 4.

 

            Well 8

Wells 8 and 1 both are interpreted as encountering transition zones, based on porosity types and log-calculated saturations. Well 8 encountered the Morrow just above the water level. Pore throats are meso- to macroporous. The two upper flow units probably are close to immobile water saturation. However, the two basal zones (3 and 4) have high saturations of mobile water. This explains why the well cut water on initial potential testing. This water production should increase with time as the water leg rises.

Figure 29 summarizes the petrophysical characteristics of well 8.

 

            Well 1

Well 1 (Figure 30) is similar to well 8, except that flow unit 2 of well 1 shows an anomalous low resistivity. The interval tested 32 bo/d and 15 Mcfg/d (5 m3 oil and 425 m3 gas per day) with no water. Therefore, the zone by definition is at immobile water saturation (Swi = 40%). The discrepancy suggests that the log resistivity was too low due to bed resolution problems. If true resistivity is 9 ohm-m2/m (used for the calculation), then the true water saturation is less than 40%.

 

            Caveat

While these petrophysical methods of analyzing wells are reliable and widely applicable in water-wet reservoirs, there is at least one source of potential error: the assumption that there are no lithologic changes that affect log-calculation parameters without affecting Previous HitpermeabilityNext Hit-porosity relationships. Examples include vuggy or fracture porosity and variable shale effects. If such changes occur, then we must modify the relationships between calculated saturations and producibility.

Back to Contents

 

Water Saturation Profile for Sorrento Field

            General Statement

Morrow Previous HitsandstoneNext Hit reservoirs reportedly display multiple oil-water contacts in several fields in the area (Sonnenberg, personal communication). Reliably recognizing separate reservoirs in a field requires considering capillary pressures, heights above free water, and observed water saturations. One convenient way to do this is to plot water saturation against structural elevation while differentiating pore throat sizes.

 

            Sw-Elevation Plot

An Sw-elevation plot (Figure 31) for study wells 4, 8, and 11 defines a trend of decreasing water saturation with increasing height. Well 1 is not on the same trend. Differences in water saturation attributable to differences in capillary pressures are apparent but are not great enough to explain the discrepancy. Ignoring possible hydrodynamic effects, the difference in trends probably represents two separate oil columns and therefore two reservoirs.

Back to Contents

 

Annotated References

Barwis, J.H., J.G. McPherson, and J.R.J. Studlick, 1989, Previous HitSandstoneNext Hit Petroleum Reservoirs: New York, Springer-Verlag, 583 p. Contains case histories of fields with reservoirs that represent each of the major depositional environments.

Beard, D.C., and P.K. Weyl, 1973, Influence of texture on porosity and Previous HitpermeabilityNext Hit of unconsolidated sand: AAPG Bulletin, vol. 57, no. 2, p. 349-369.

Burley, S.D., J.D. Kantorowicz, and B. Waugh, 1985, Clastic diagenesis, in P.J. Brenchley and B.P.J. Williams, eds., Sedimentology: Recent Developments and Applied Aspects: London, Blackwell Scientific Publications, p. 189-228.

Choquette, P.W., and L.C. Pray, 1970, Geologic nomenclature and classification of porosity in sedimentary carbonates: AAPG Bulletin, vol. 54, no. 2, p. 207-250. Classic reference for basic concepts regarding carbonate porosity.

Coalson, E.B., D.J. Hartmann, and J.B. Thomas, 1990, Applied Petrophysics in Exploration and Exploitation: Notes Previous HitfromNext Hit short course sponsored by Univ. of Colo.-Denver, var. pages.

Galloway, W.E., 1984, Hydrogeologic regimes of Previous HitsandstoneNext Hit diagenesis, in D.A. McDonald and R.C. Surdam, eds., Clastic Diagenesis: AAPG Memoir 37, p. 3-14.

Galloway, W.E., and D.K. Hobday, 1983, Terrigenous Clastic Depositional Systems: Applications to Petroleum, Coal, and Uranium Exploration: New York, Springer-Verlag, 438 p. Summarizes reservoir characteristics of major Previous HitsandstoneNext Hit depositional environments, especially with respect to sand body geometries.

Harrison, W.J., and R.N. Tempel, 1993, Diagenetic pathways in sedimentary basins, in A.D. Horbury and A.G. Robinson, eds., Diagenesis and Basin

Hartmann, D.J., and E.B. Coalson, 1990, Evaluation of the Morrow Previous HitsandstoneNext Hit in Sorrento field, Cheyenne County, Colorado, in S.A. Sonnenberg, L.T. Shannon, K. Rader, W.F. von Drehle, and G.W. Martin, eds., Morrow Sandstones of Southeast Colorado and Adjacent Areas: RMAG Symposium, p. 91-100.

Hayes, J.B., 1983, Previous HitSandstoneNext Hit diagenesis as an exploration tool: AAPG Clastic Diagenesis School, June 27-July 1, Monterey, California.

James, S.W., 1989, Diagenetic history and reservoir characteristics of a deep Minnelusa reservoir, Hawk Point field, Powder River basin, Wyoming, in E.B. Coalson, S.S. Kaplan, C.W. Keighin, C.A. Oglesby, and J.W. Robinson, eds., Petrogenesis and Petrophysics of Selected Previous HitSandstoneNext Hit Reservoirs of the Rocky Mountain Region: RMAG Symposium, p. 81-96.

_____, M.M. Dodge, and W.E. Galloway, 1984, Regional controls on diagenesis and reservoir quality in Lower Tertiary sandstones along the Texas Gulf Coast, in

Muller, M.M., and E.B. Coalson, 1989, Diagenetic and petrophysical variations of the Dakota Previous HitsandstoneNext Hit, Henry field, Green River basin, Wyoming, in E.B. Coalson, S.S. Kaplan, C.W. Keighin, C.A. Oglesby, and J.W. Robinson, eds., Petrogenesis and Petrophysics of Selected Previous HitSandstoneNext Hit Reservoirs of the Rocky Mountain Region: RMAG Symposium, p. 149-158.

Neasham, J.W., 1977, The morphology of dispersed clay in Previous HitsandstoneNext Hit reservoirs and its effect on Previous HitsandstoneNext Hit shaliness, pore space, and fluid flow properties: Proceedings of the SPE Annual Meeting, October 9-12, paper SPE-6858.

North, F.K., 1985, Petroleum Geology: London, Allen & Unwin, 607 p.

Patchett, J.G., and E.B. Coalson, 1982, The determination of porosity in Previous HitsandstoneNext Hit and shaly Previous HitsandstoneNext Hit, part 2: effects of complex mineralogy and hydrocarbons: 23rd Annual SPWLA Logging Symposium, July 6-9, paper T, 50 p.

Pittman, E.D., 1992, Relationship of porosity to Previous HitpermeabilityNext Hit to various parameters derived Previous HitfromNext Hit mercury injection-capillary pressure curves for Previous HitsandstoneNext Hit: AAPG Bulletin, vol. 76, no. 2, p. 191-198.

Scherer, M., 1987, Parameters influencing porosity in sandstones: a model for Previous HitsandstoneNext Hit porosity prediction: AAPG Bulletin, vol. 71, no. 5, p. 485-491.

Shelley, R.C., 1985, Elements of Petroleum Geology: San Francisco, W.H. Freeman, 449 p.

Sneider, R.M., and H.R. King, 1984, Integrated rock-log calibration in the Elmworth field, Alberta, Canada: part I: reservoir rock detection and characterization, in J.A. Masters, ed., Elmworth--Case Study of a Deep Basin Gas Field: AAPG Memoir 38, p. 205-214.

Sonnenberg, S.A., 1985, Tectonic and sedimentation model for Morrow Previous HitsandstoneNext Hit deposition, Sorrento field area, Denver basin, Colorado: The Mountain Geologist, October, p. 180-191.

Stonecipher, S.A., and J.A. May, 1990, Facies controls on early diagenesis: Wilcox Group, Texas Gulf Coast, in D. Meshri and P.J. Ortoleva, eds., Prediction of Reservoir Quality Through Chemical Modeling, I: AAPG Memoir 49, p. 25-44.

Stonecipher, S.A., R.D. Winn, Jr., and M.G. Bishop, 1984, Diagenesis of the Frontier Formation, Moxa Arch: a function of Previous HitsandstoneNext Hit geometry, texture and composition, and fluid flux, in D.A. McDonald and R.C. Surdam, eds., Clastic Diagenesis: AAPG Memoir 37, p. 289-316.

Surdam, R.C., T.L. Dunn, D.B. MacGowan, and H.P. Heasler, 1989, Conceptual models for the prediction of porosity evolution with an example Previous HitfromNext Hit the Frontier Previous HitSandstoneNext Hit, Big-horn basin, Wyoming, in E.B. Coalson, S.S. Kaplan, C.W. Keighin, L.A. Oglesby, and J.W. Robinson, eds., Previous HitSandstoneNext Hit Reservoirs: Rocky Mountain Association of Geologists, p. 7-21.

Thomas, L.K., P.L. Katz, and M.R. Tek, 1968, Threshold pressure phenomena in porous media: SPE Journal, June, p. 174-184.

Wilson, M.D., 1994a, Non-compositional controls on diagenetic processes, in M.D. Wilson, ed., Reservoir Quality Assessment and Prediction in Clastic Rocks: SEPM Short Course 30, p. 183-208. Discusses the effect that variables such as temperature and pressure have on diagenesis of sandstones. A good reference for predicting Previous HitsandstoneTop reservoir system quality.

_____, 1994b, Assessing the relative importance of diagenetic processes and controls, in M.D. Wilson, ed., Reservoir Quality Assessment and Prediction in Clastic Rocks: SEPM Short Course 30, p. 259-276.

_____ and E.D. Pittman, 1977, Authigenic clays in sandstones: recognition and influence on reservoir properties and paleoenvironmental analysis: Journal of Sedimentary Petrology, vol. 47, no. 1, p. 3-31.

Back to Contents