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Lithology and rock type determination

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The identification of a bed’s lithology is fundamental to all reservoir characterization because the physical and chemical properties of the rock that holds hydrocarbons and/or water affect the response of every tool used to measure formation properties. Understanding reservoir lithology is the foundation from which all other petrophysical calculations are made. To make accurate petrophysical calculations of porosity, water saturation (Sw), and permeability, the various lithologies of the reservoir interval must be identified and their implications understood. Lithology means "the composition or type of rock such as sandstone or limestone." [1] These few words belie a host of details about reservoir rocks:

  • Their depositional and diagenetic history
  • Pore structure
  • Mineralogy

Definitions

The term lithology is used as a gross identification for a rock layer in the subsurface and uses familiar names such as:

  • Sandstone (or sand)
  • Limestone
  • Dolostone (or dolomite)
  • Claystone (or clay)
  • Chert
  • Coal
  • Shale (or mudrock)
  • Diatomite
  • Halite
  • Anhydrite
  • Gypsum
  • Tuff

(The preceding list is not exhaustive. For detailed lists, see Deeson[2])

The term rock type is a more detailed description than lithology because it reflects the natural groupings of pore systems that produce recognizable properties used to predict:

  • Flow properties
  • Volumes
  • Fluid saturations

Lithology focuses on grains, while rock type focuses on pores. The list of rock types contains more than 250 classifications. [Personal communication with R.M. Sneider, R.M. Sneider Exploration Inc., Houston (1990).]

Another term used in the literature is the Greek equivalent "petrofacies." (Another term that is finally dropping from use is the incorrectly named "electrofacies.")

Direct determination

Obtaining a physical sample of the reservoir is the surest way to unambiguously determine lithology and rock type, but obtaining this physical sample is not always easy. Mud logs are the first choice in wildcat wells, but exact assignment of a rock fragment to a particular depth is not without error. The size of the individual rock sample examined at the surface is rather small because it is limited by the size of drill cuttings and rock strength. Weak rocks, ones without cement, are often reduced to original detrital grain size by the drilling process, making it difficult to determine rock type, but still possible to determine lithology. Once the well is drilled and logged and rock layers are marked for further study, rock samples can be obtained through the use of wireline core takers or sidewall core drills.

Recovery of sidewall samples is not always a sure thing, and we often fail to get rock samples from zones of interest. In a wildcat well with a zone of high interest identified with logs, rock samples, and fluid samples, we can plug back the well several hundred feet, set a whipstock, perform a parallel sidetrack (called a bypass hole), and then take a whole core across the zone of interest. Because the two holes are parallel, we know exactly at which depth to swap out the drill bit with a core barrel. The resulting whole core can be sampled, and sophisticated core analysis can be used to identify the rock type of each zone and determine petrophysical parameters, which are used to refine the formation evaluation from the log data.

Indirect determination

If no direct rock sample is available in a given zone, log responses must be used alone to simultaneously determine lithology, porosity, and fluid saturations. Rock typing is much more involved and requires the use of commercially available catalogs of analog data[3][4] or locally collected data to pinpoint petrophysical properties that can be used to refine porosity and fluid-saturation calculations. If, in a given wellbore, one is lucky enough to encounter parts of the desired reservoir below the free-water level, then fluid saturation is known and gross lithology can be determined from routine wireline logs such as density, neutron, and acoustic tools. All wireline service companies provide charts and answer products that convert wireline logging data into lithology; however, few beds are simple homogeneous layers (See article on reservoir geology). If some of the layers are beneath the resolving thickness of the tool, some average response of the layers, depending on bed and borehole geometry, can be observed. Single layers of salt (NaCl), anhydrite, gypsum, coal, or tuft are easily identified when several feet thick or thicker; however, salt-plugged sandstone can mimic gas-filled clean sandstone, or a very shaly rock type can hide the presence of gas.

Mica or potassium feldspar, when abundant in sandstones, can confuse lithology determination on the basis of the gamma ray (GR) response. The more sophisticated GR spectroscopy tools can help to identify the chemical species in a given rock and often can lead to deducing its lithology. (See the page on nuclear logging). However, no single wireline log or set of logs can determine pore size distribution and pore throat size distribution. These data are used to establish rock type, resulting fluid flow characteristics, and other petrophysical parameters needed to determine fluid saturation. If every reservoir in our wildcat well is hydrocarbon filled, the problem of quantification becomes more difficult, particularly when formation water resistivity, Rw, is unknown. In difficult areas, a follow-up well and a whole core, drilled with oil-based mud that is taken high in the hydrocarbon column, must be drilled to guarantee no in-situ water displacement. Subsequent sophisticated core analysis can determine the value of in-situ water salinity. If coring is not an option, a well will have to make a significant amount of water to test. In pressure-depletion reservoirs that never produce much water, the accurate determination of water salinity may never happen if the reservoir is drilled with oil-based mud, negating the use of the spontaneous potentials (SP) log.

Use of acoustic logs

Acoustic velocity is primarily a function of the rock matrix and can be used to identify different lithologies and for stratigraphic correlations. A variety of crossplot techniques, using acoustic measurements alone, or in combination with other porosity logs (neutron and density), have been devised to assist in lithologic identification (Fig. 1). In particular, the M-N and mineral-identification-plot (MID) techniques use all three porosity logs in different combinations.[5][6] Before lithology determination, the individual log measurements must be corrected for influences of:

  • Gas effect
  • Secondary porosity
  • Bad hole conditions
  • Shaliness

In general, the MID plot is more sensitivity to lithology, gas, and secondary porosity and provides superior results to M-N plots. Crossplots, using a variety of log measurements or combinations of measurements can be used to resolve specific lithologic problems related to local or regional geology.[7][8]

The ratio of compressional to shear velocity, Vp/Vs, is an effective lithology indicator because each lithology exhibits a defined trend that is independent of porosity and depth (Fig. 2).[9][10][11] However, because the Vp/Vs ratio is affected by formation anisotropy, the ratio values may not be absolute indicators of a particular lithology.[12]

The addition of shear slowness to lithology identification provides a more robust result that can be particularly useful in cased-hole evaluations where density logs are not available. In Fig. 3, the combined use of shear slowness and cased-hole neutron porosity results in enhanced-porosity determination in a complex lithology. Crossplots of Vp/Vs ratio vs. compressional travel time, Δtc, facilitate identification of lithology trends with respect to porosity and lithology (Fig. 4[13]). Recent studies of complex carbonate reservoirs indicate that the Vp/Vs ratio is a function of porosity and in some cases, can differentiate higher-permeability facies.[14][15]

Determining lithology

Geologists are trained to describe rocks, based on:

  • Outcrops
  • Cuttings
  • Cores
  • More-detailed mineralogical measurements

They identify certain log-curve characteristics related to particular depositional environments; for example:

  • Coarsening upwards
  • Fining upwards
  • Massive bedding
  • The scales of interbedding

For reservoir petrophysical evaluations, a geologist must be on the technical team, and there must be cooperation between the geologists and engineers.

The lithology of a new oil or gas reservoir is understood on a preliminary basis by the wellsite geologist’s description of mud-shaker cuttings and possibly by a few cores that are cut if the reservoir interval is sufficiently long. Lithology is also determined from the logs, because each main reservoir lithology has characteristic responses. Frequently, lithologies are derived by pattern recognition of the GR-, density-, and neutron-log responses.

Some subsequent delineation wells are likely to be cored over the entire of the reservoir interval. The geologist will make detailed descriptions of these cores and order a number of thin-section, scanning electron microscope (SEM), X-ray diffraction (XRD), and mercury-injection capillary pressure (MICP) or pore-size measurements on various rock types that have been identified. From these data and the routine-core-analysis data, geologists can construct their interpretation of the reservoir’s depositional environment and insights into the nature of its pore system and mineralogy. Geologists typically prepare reservoir cross sections with seismic traces, well logs, and core descriptions to illustrate the depositional environments, rock types, and internal geometries. See the reservoir geology page for additional discussion of geologic aspects of oil and gas reservoirs.

The lithology of a reservoir impacts the petrophysical calculations in numerous ways. The depositional environment and sediments being deposited will define the grain size, its sorting, and its distribution within the reservoir interval. In most sandstone reservoirs, the depositional environment controls the porosity/permeability relationship.

The mineralogy of a reservoir results from a combination of its depositional and diagenetic histories. For a sandstone reservoir, the depositional environment controls the percentages of:

  • Quartz
  • Chert
  • Feldspar
  • Detrital clay-mineral grains and the other matrix material

These materials must be measured and their variations within the reservoir interval quantified. The diagenetic history determines the extent to which:

  • Portions of the grains have been leached away
  • Cements such as calcite, siderite, or pyrite have been deposited
  • Authigenetic clay minerals formed.

The diagenetic history can be complicated and can be impacted by differences in burial history from one part of a reservoir to other parts, or by aspects of the hydrocarbon-filling history.

For carbonate reservoirs, most of the same factors as discussed for sandstones come into play, but the mineralogical considerations are different. For carbonate formations, the rock formations typically consist of interbedded sequences of carbonates, dolomites, anhydrite, salt, and shale layers. The keys to reservoir development within the carbonate layers are the original grain size and how it has been altered by chemical diagenetic processes. As these chemical reactions take place, the pore-size distribution and porosity level will change (e.g., by dolomitization). Carbonate-reservoir porosity is also greatly enhanced by weathering, dissolution, and fracturing.

As well as the basic mineralogy, clay-mineral properties are also of particular importance to the petrophysical calculations in the reservoir intervals. There are many types of clay minerals, and their impacts on well logs are quite different. Particularly, there may be differences between clay minerals that form shale layers and claystones and those that occur within sandstone intervals. While the detrital clay minerals in sandstones will likely be the same as the clay minerals in the shales, the authigenetic clay minerals in the sandstone pore system can be quite different. The types and amounts of the various clay minerals impact the rock pore system by affecting its electrical properties and permeability characteristics. A few of the aspects of mineralogy that impact the petrophysical calculations are the extent to which:

  • Various heavy minerals impact the density log, for example:
    • Anhydrite
    • Calcite
    • Dolomite
    • Granites
    • Pyrite
    • Siderite
  • Various light minerals impact the density, neutron, and sonic logs, like:
    • Coal
    • Halite salt
  • Various radioactive minerals impact the GR log, such as:
    • Uranium
    • Thorium
    • Potassium salts such as K-feldspar
  • Various electrically conductive minerals impact the resistivity logs, like:
    • Clay minerals
    • Pyrite

Clay-mineral properties

Clay minerals are, in general, composed of layered alumina and silicate molecules, [16][17][18] and the properties of the various clay minerals vary widely. Some swell when wet, are plastic, and can easily deform, while others are hard and dense. Clay minerals are extremely fine-grained, and those with the smallest grain size have a very high surface-area-to-volume ratio. Clay minerals (e.g., chlorite, illite, kaolinite, smectites, and mixed-layer clays) generally impair the permeability and porosity of the pores in which they reside; the permeability is sometimes impacted by an order of magnitude or more. However, it is the smectites (one of which is montmorillonite) that often cause very significant effects on the petrophysical measurements of porosity and water saturation.

In smectites, exchange cations and adsorbed water molecules are loosely bound between the silicate layers. Dehydration occurs whenever there is low humidity or an elevated temperature (e.g., in a dried-up lakebed or in a brick kiln). Loss of this adsorbed water is even more rapid at temperatures above the boiling point of water. For smectites, this is a problem during core analysis because the extraction and drying of the core samples is an essential step in the measurement procedures.

For resistivity logging, smectite clay minerals pose a further problem. The exchange cations and adsorbed water molecules lead to smectite exhibiting excess electrical conductivity. This occurs as exchange cations (e.g., sodium, calcium) migrate from site to site on the clay surfaces. The clays thus exhibit a lower resistivity and, in most cases, depress the bulk resistivity of reservoir rocks in which they reside. Cation exchange also occurs with the other clay minerals, but to a lesser extent.

Rock formations of pure clay minerals are rare. More typically, several species of clay mineral are associated together with clay-sized and silt-sized quartz, mica, and other rock grains. This association is known widely as "shale." In sandstone reservoirs, clay-mineral content typically ranges from 0 to approximately 10% BV. In shales, clay minerals occupy approximately 20 to 40% BV, and the remainder is often very-fine-grained quartz, volcanic minerals, carbonates, and organic matter. Besides the adsorbed water on the clay minerals, shales and authigenetic clay minerals also include additional formation water held in their micron-sized pore system by capillary retention. This water cannot be produced from the formation and is referred to as "capillary water."

During the burial of the sediments over geological time, the overburden stress and the pore-fluid pressures increase. The net result is that water is expelled from the shale beds into surrounding permeable beds. Young clay-mineral-bearing sediments at shallow burial depths are likely to be smectites (e.g., gumbo shale in the submerged Mississippi delta of Louisiana, US). Clay minerals in deeply buried shales become less hydrated, and their forms can be altered by higher temperatures and pressures. Low-salinity water is sometimes observed in reservoir-rock pores adjacent to the shales and where clay-mineral-expelled water cannot escape from the permeable bed. This formation may become overpressured and can cause severe problems during drilling if not predicted or detected in time to alter the drilling program.

Although shale formations are not usually of commercial importance, the measurement and evaluation of core and log data in partly shaly reservoirs presents many difficulties that are not present in clay-mineral-free (clean) formations. A large body of technical literature addresses shaly-formation analysis because the shale, to one degree or another, affects all log and core measurements. Because these shaly rocks are so variable, a single model usually cannot fully describe all of their behaviors.

Reservoirs with a fractional shale content, Vsh, are common, and the clay minerals/shales take several physical forms, including laminated, structural, and pore-filling. [19][20] Laminated shales are thin detrital shale layers interbedded within a reservoir interval. Each represents short periods of deposition where the suspended finest sediments could settle out of the original sediment-rich river, lake, or seawater. Laminated shales may range from approximately one hundredth of a centimeter to 1 m thick. Shale deposits can be broken up and reworked after their original deposition and become "grains" in the same manner as quartz grains. Structural, or detrital, shale grains become a part of the grain composition of sandstone. As well as the clay minerals that are deposited directly as solids from lakes and marine environments, they also may be deposited from in-situ formation-water solutions that are rich in dissolved minerals. These clay minerals are called "authigenetic." By this mechanism, the pores of sandstone may become partly filled with various clay minerals and other minerals. Of this type, illite, kaolinite, chlorite, and smectite clays are most common. Each can take several physical and chemical forms within a pore. Several generations of pore-filling clay minerals may be present, representing different periods of geological time when changes occurred in formation-water composition or depth of burial.

Evaluation of shale volume

Geological techniques, like XRD, are available to identify clay-mineral species and to quantify rock-component volumes in physical specimens. Such analyses can help calibrate the log-based methods for estimating Vsh, the bulk-volume fraction of shale. Vsh from the GR log is frequently used to determine nonpay.

Shale content can be estimated from well logs by many techniques, because shale affects the readings of most logs. The task for a particular field is to identify an evaluation technique that is reasonably accurate and as simple as possible. A method using a combination of the neutron and density logs is often applied for practical log analysis. Modern optimized simultaneous-equations log solutions[21] attempt to identify individual clay species. Nevertheless, for petrophysical studies for field development, it is the GR log that is probably used most frequently to evaluate Vsh. The GR-log readings are normalized to reduce hole-size variations and mud effects and differences among the tools. Normalization is achieved by finding typical GR values in the 100% "clean" sand and 100% shale formations for each well. These different endpoint values in each well are then equalized. The GR values in between the sand and shale levels are scaled to give Vsh values. The scaling is often linear, but nonlinear alternatives are available, if appropriate. Occasionally the GR log is affected by radioactive components that are not shale, and these need to be identified and assigned a revised Vsh. Water-based drilling muds sometimes contain high concentrations of potassium salts, and these may also lead to GR interpretation problems, such as invasion of potassium salts into the near-wellbore region.

The uncertainty of Vsh log evaluations is moderate to high. At low values, less than 30% BV, the authors estimate that Vsh may typically be accurate to approximately ± 10% BV at one standard deviation (SD). At values greater than 30% BV, the uncertainty increases. The uncertainties affect nonpay bed-boundary evaluations; however, the Vsh uncertainty also seriously impacts the accuracy of the effective-porosity and Sw estimates when smectites, with their high clay-mineral adsorbed-water fraction, are present. If the clay species is different (illite or chlorite with little or no adsorbed water), then the Vsh uncertainty has a much-reduced impact on porosity, as is discussed in the core/log calculation approaches.

Reservoir zonation or layering

An important conclusion from the geologists’ technical studies is a definition of the extent to which the reservoir needs to be subdivided either vertically or areally. Besides all of the information developed by the geologists from the detailed core descriptions, the routine-core-analysis and SCAL data need to be analyzed for such effects. This is accomplished by preparing, for different possible layering within the reservoir interval, a variety of crossplots such as log10 (permeability) vs. porosity and OBM-core Sw vs. porosity or log10 (permeability) and comparing the data clouds and trends of those plots from one possible layer to the next. Significant differences should be expected between reservoir intervals with different depositional environments and differences in grain size and sorting. Areal variations may occur across a given vertical zone within the reservoir because of varying distances from the sediment source, differences in the depositional environment in various areas, or varying diagenetic effects.

For accurate petrophysical calculations, most large reservoirs will probably require a number of vertical subdivisions, usually termed zones or layers. Typical zones for a reservoir are 50 to 150 ft (15 to 45 m) thick. Areally, several square miles of reservoir can usually be included together; however, if the reservoir covers tens of square miles, it is likely to require some areal subdivision for accurate petrophysical calculations.

A second consideration is the amount of available data of various types. If a reservoir has a large database of log and core data from many wells, then the number of these subdivisions is not impacted by the quantity of data. However, if some types of data are very limited, then this consideration may control the degree of vertical and areal subdivision that can be used for various petrophysical calculations. The same degree of subdivision may not be required for net-pay calculations relative to porosity calculations or for porosity calculations relative to Sw calculations. In summary, more-accurate vertical and areal petrophysical calculations are made if the reservoir is appropriately subdivided. [22][23] Fig. 5 shows the vertical zonation used for the Prudhoe Bay field’s Sadlerochit reservoir. Figs. 6 through 8 are example plots based on real reservoir data that show how rock properties within the same field can vary from one reservoir to another and from one vertical portion of a reservoir interval to other parts.

References

  1. Hynes, N.J. 1991. Dictionary of Petroleum Exploration, Drilling, and Production. Tulsa, Oklahoma: PennWell.
  2. Deeson, A.F.L. 1973. The Collector’s Encyclopedia of Rocks & Minerals. New York City: Clarkson N. Potter Inc.
  3. A Catalog of Petrophysical and Geological Properties of Typical Reservoir Rocks. 1995. Houston: Shell Oil Co.
  4. The World Wide Rock Catalog. 1990. Houston: Reservoirs Inc.
  5. Burke, J.A., Campbell Jr., R.L., and Schmidt, A.W. 1969. The Litho-Porosity Cross Plot a Method of Determining Rock Characteristics for Computation of Log Data. Presented at the SPE Illinois Basin Regional Meeting, Evansville, Indiana, 30-31 October. SPE-2771-MS. http://dx.doi.org/10.2118/2771-MS
  6. Clavier, C. and Rust, D.H. 1976. MID Plot: A New Lithology Technique. The Log Analyst 17 (6): 16–24.
  7. Fertl, W.H. 1981. Openhole Crossplot Concepts A Powerful Technique in Well Log Analysis. J Pet Technol 33 (3): 535-549. SPE-8115-PA. http://dx.doi.org/10.2118/8115-PA
  8. Robert, H.V. and Campbell, R.L. Jr. 1976. Applications of CORIBAND to the Evaluation of Sandstones Containing Mica. The Log Analyst 17 (1): 33–40.
  9. 9.0 9.1 Pickett, G.R. 1963. Acoustic Character Logs and Their Applications in Formation Evaluation. J Pet Technol 15 (6): 659-667. SPE-452-PA. http://dx.doi.org/10.2118/452-PA.
  10. Nations, J.F. 1974. Lithology and Porosity from Acoustic Shear and Compressional Wave Transit Time Relationships. The Log Analyst 15 (6): 3–8.
  11. Eastwood, R.L. and Castagna, J.P. 1987. Interpretation of V p  /V s Ratios from Sonic Logs. Shear-Wave Exploration, S.H. Danbom and S.N. Domenico eds., 139-153. Tulsa, Oklahoma: SEG, Geophysical Development Series No. 1.
  12. Johnston, J.E. and Christensen, N.I. 1993. Compressional to Shear Velocity Ratios in Sedimentary Rocks. Intl. J. of Rock Mechanics and Mining Sciences and Geomechanical Abstracts 30 (7): 751–754.
  13. Zhang, T., Tang, X.M., and Patterson, D. 2000. Evaluation of Laminated Thin Beds in Formations Using High-Resolution Acoustic Slowness Logs, paper XX. Trans., 2000 Annual Logging Symposium, SPWLA, 1–14.
  14. Assefa, S., McCann, C., and Sothcott, J. 2003. Velocities of Compressional and Shear Waves in Limestone. Geophysical Prospecting 51 (1): 1–13.
  15. Tsuneyama, F. et al. 2003. Vp/Vs Ratio as a Rock Frame Indicator for a Carbonate Reservoir. First Break 21 (7): 53–58.
  16. Theys, P.P. 1999. Log Data Acquisition and Quality Control, second edition. Paris, France: Editions Technip.
  17. Hensel Jr., W.M. 1982. An Improved Summation-of-Fluids Porosity Technique. Society of Petroleum Engineers Journal 22 (2): 193-201. SPE-9376-PA. http://dx.doi.org/10.2118/9376-PA
  18. Brown, G. 1961. The X-Ray Identification and Crystal Structures of Clay Minerals. London: Mineralogical Soc. Clay Minerals Group.
  19. Log Interpretation Principles/Applications. 1989. Houston, Texas: Schlumberger.
  20. Fundamentals of Rock Properties. 2002. Aberdeen: Core Laboratories UK Ltd.
  21. Mezzatesta, A., Rodriguez, E., and Frost, E. 1988. Optima: A Statistical Approach to Well Log Analysis. Geobyte (August).
  22. Sneider, R.M. and Erickson, J.W. 1994. Rock Types, Depositional History, and Diagenetic Effects, Ivishak Reservoir, Prudhoe Bay Field. SPE Res Eng 12 (1): 23–30. SPE-28575-PA. http://dx.doi.org/10.2118/28575-PA
  23. 23.0 23.1 Holstein, E.D. and Warner, J., H. R. 1994. Overview of Water Saturation Determination For the Ivishak (Sadlerochit) Reservoir, Prudhoe Bay Field. Presented at the SPE Annual Technical Conference and Exhibition, New Orleans, Louisiana, 25-28 September 1994. SPE-28573-MS. http://dx.doi.org/10.2118/28573-MS

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See also

Petrophysics

Acoustic logging

PEH:Petrophysics

PEH:Petrophysical_Applications