The term "petrophysics" was coined by G.E. Archie and J.H.M.A. Thomeer in a quiet bistro in The Hague. By their definition, petrophysics is the study of the physical and chemical properties of rocks and their contained fluids.
Role of petrophysicist
Petrophysics emphasizes those properties relating to the pore system and its fluid distribution and flow characteristics. These properties and their relationships are used to identify and evaluate:
- Hydrocarbon reservoirs
- Hydrocarbon sources
The petrophysicist or petrophysical engineer practices the science of petrophysics as a member of the reservoir management team. The petrophysicist provides answers on products needed and used by team members, as well as physical and chemical insights needed by other teammates.
The reservoir and fluid characteristics to be determined are:
- Thickness (bed boundaries)
- Lithology (rock type)
- Fluid saturations and pressures
- Fluid identification and characterization
- Permeability (absolute)
- Fractional flow (oil, gas, water)
It is easy to define these characteristics and to appreciate their part in the assessment of reserves. The difficult part comes in determining their actual value at a level of certainty needed to make economic decisions leading to development and production. The seven characteristics listed are interdependent (i.e., to properly determine porosity from a wireline log, one must know the lithology, fluid saturations, and fluid types). The science of petrophysics is then used to unscramble the hidden world of rock and fluid properties in reservoirs from just below the Earth’s surface to ones more than four miles deep. The petrophysicist then takes on many characteristics of the fictional sleuth Sherlock Holmes to extrapolate, from the most meager of clues, the true picture of the subsurface reservoir using dogged determination to wrest all possible information from the available data, all the while enjoying the thrill of the hunt.
How does the petrophysicist solve this difficult problem? Archie’s general method is to subdivide the problem into smaller segments and iterate using all data until all data agree. One starting point is to determine rock types (petrofacies) wherein we identify:
- Pore type
- Pore size distribution
- Pore throat type
- Pore throat distribution
When coupled with fluid type, one can establish a capillary pressure model that will lead to understanding in-situ fluid saturations and fluid flow. However, the tools available to the petrophysicist are:
- Mud logging (solids, liquids, gasses, volumes, rates, concentrations, and temperature)
- Measurement while drilling (MWD) and Logging while drilling (LWD)
- Wireline logging (open- and cased-hole)
- Core sampling [(wireline (percussion and drilled) and whole] and core analysis
- Fluid sampling (wireline and/or drillstem tests)
This list is arranged in order of the usual acquisition sequence. The economics of a given evaluation may restrict the application of any of these tools.
Choosing the right tools
The choices of tools for the evaluation program are usually made by the reservoir management team with recommendations from the petrophysicist. Cost and accuracy are usually highly correlated; thus, the team’s choices quickly become one of finding the maximum allowable risk for the minimum cost (time and money) of the evaluation. Table 1 summarizes the typical evaluation program choices and can be used as a reference during subsequent discussions on determination of various reservoir properties.
This wiki contains additional information on the properties listed in the table.
Development petrophysics emphasizes the integration of core data with log data; the adjustment of core data, when required, to reservoir conditions; and the calibration and regression line-fitting of log data to core data. The goal of the calculations is to use all available data, calibrated to the best standard, to arrive at the most accurate quantitative values of the petrophysical parameters (i.e., lithology, net pay, porosity, water saturation, and permeability).
In practical terms, petrophysics is used for two types of calculations: determination of original hydrocarbons in place [original oil in place (OOIP) or original gas in place (OGIP)] and their distribution, and reservoir-engineering dynamic flow calculations. For the development geoscientists (geologists, geophysicists, and geostatisticians), petrophysics means developing the detailed stratigraphic, depositional, and diagenetic descriptions of the reservoir, both vertically and areally. To make accurate calculations of OOIP or OGIP and the various flow calculations, accurate foot-by-foot calculations of lithology, net pay, porosity, water saturation, and permeability are necessary. These calculations need to be made not only as overall calculations, but also so that the variation and distribution of these parameters are determined appropriately.
Some of the petrophysical calculations can be made in several ways, particularly for porosity and water saturation. One key to arriving at an accurate petrophysical calculation is to obtain the same quantitative result with a variety of techniques. An important consideration is the acquisition and handling of the various types of petrophysical data and, for each reservoir, the preparation of its unique petrophysical database. Petrophysical data take many forms and, for many reservoirs, may not be as comprehensive as desired. The technical personnel working with these data have to review what data are available, their quality, and what additional data might be acquired from the existing wellbores and from preserved and unpreserved cores. Finally, if there are sufficient financial stakes, new wells might be drilled, cores cut, various additional sample measurements made, and both conventional and special logs run to obtain other desired petrophysical information.
Log analysis is used universally and is generally successful in the identification of oil and gas reservoirs and in the preliminary estimation of their volumes.  However, log analysis augmented and calibrated with core and other data provides the most accurate quantification of oil and gas volumes present in a well and best represents the practice of petrophysics.
The description of petrophysical calculations are focused at the reservoir level, where there are several to hundreds of wells with logs and significant amounts of core data that need to be integrated to develop the most accurate overall values for the petrophysical parameters over the whole of the reservoir. The techniques discussed also apply to single wellbores, but many of the complications are not a concern in single-well evaluation. Some special cases, such as oil shales, tight gas-sand reservoirs, or coalbed-methane reservoirs, may require different calculations that those used for more typical oil and gas reservoirs.
Petrophysical property determination
Petrophysical analysis can be used for the following:
Applying petrophysical techniques
The pages linked above will acquaint the reader with the various aspects of the quantitative petrophysical determination of lithology, net pay, porosity, fluid contacts, water saturation, and permeability. To make these calculations as accurately as possible, core and log data need to be integrated. The routine-core-analysis data adjusted to reservoir conditions should be used to calibrate the logs for more-accurate calculations at the various wells. In applying petrophysical techniques it is valuable to remember:
- Lithology is determined by geologists working with cores and rock cuttings. This information can be combined with log characteristics to identify depositional environments and characterize how these change vertically and areally throughout the reservoir.
- The clay minerals present in the shales and the sandstone intervals, both as detrital and authigenic components, must be identified and quantified so that their effects on the logs and routine-core-analysis data can be adequately understood. Radioactive components present in the reservoir rocks must be identified and quantified so that the clay-mineral volumes derived from the GR log are not overstated.
- Net pay calculations determine how much of the reservoir interval contributes to the technical calculations of in-place hydrocarbon volumes and fluid flow. With modern reservoir engineering tools, it is possible to set N/G to 1.0 and work the various engineering calculations from that basis. If some portion of the reservoir interval is to be excluded as nonpay, the choice of cutoff should be based on flow considerations with a systematic and consistent approach. Whatever nonpay cutoff is used, that cutoff will be somewhat arbitrary.
- Porosity can be computed from a variety of well logs (density, sonic, or neutron) in combination with routine-core data adjusted to reservoir conditions. In sandstones in which the mineralogy and the hole conditions permit, foot-by-foot porosity calculations from the density log, calibrated to core, are likely to be the most accurate. Correct fluid values are an integral part of the log evaluation. Porosity needs to be calculated accurately because, as well as its primary use, these values are also required for Sw and permeability estimates used directly in the volumetrics and flow calculations. Minerals that affect the porosity calculations, such as clay and heavy minerals, need to be identified as part of the lithology determination.
- Water saturation can be computed by a number of independent methods using routine-core-analysis oil-based mud (OBM)-core Dean-Stark Sw data, special-core-analysis (SCAL) capillary pressure data, resistivity logs used in combination with SCAL rock electrical-property measurements, or some combination of these three datasets. Adjusted OBM-core Dean-Stark S w data are likely to be the most accurate method. Integrated use of these various technical approaches will result in the most accurate Sw solution overall. The relevant uncertainty here is not in Sw itself; it is the uncertainty in the complement, the hydrocarbon saturation (1 − Sw), that is important.
- In the water-saturation calculation using resistivity logs, the connate-brine salinity and its resistivity, Rw, can vary within the hydrocarbon column, but the extent of this variation is often not measured. Also, the rock electrical properties may be a function of Sw. In most conventional Sw calculations using well logs, these are both assumed to be constant, and those assumptions can lead to significant errors in the calculated Sw values. The Sw calculations from the resistivity logs and the various Archie parameters can be partially checked in aquifer intervals where Sw is known to be 100% PV.
- In the Sw calculation using Pc measurements, the laboratory tests are measurements of fluid volumes associated with cleaned and restored core plugs. For application, the reservoir values of the interfacial-tension (IFT), contact angle, and the wetting state of the reservoir generally must be estimated, along with several other factors. Pc laboratory tests do not always achieve the equilibrium water saturation, or the same water distribution within the pore network as is present in the real reservoir.
- Permeability is typically calculated from porosity logs through a permeability/porosity transform. Permeability values need to be adjusted to reservoir conditions. This adjustment is nonlinear, with poor-quality rocks having larger adjustments compared with those applied to high-quality rocks. Also, the calculated permeabilities at the wells should be compared with those obtained from pressure-buildup (PBU) analysis of flow tests.
- The statistical correlation and calibration of core and log data requires that these data are properly depth aligned, have outliers deleted, and, if required, are mathematically transformed. A variety of line-fitting techniques are available, but the "y-on-x" approach generally results in the most accurate predictor, except in highly variable, heterogeneous rocks.
- In any reservoir with a thick hydrocarbon column and large areal extent, more accurate-petrophysical calculations are made if the reservoir is vertically zoned or layered. Different parameters for different areas of the reservoir may also be required for the most accurate solution.
- ↑Thomas, E.C. 1992. 50th Anniversary of the Archie Equation: Archie Left More Than Just an Equation. The Log Analyst (May–June) 199.
- ↑Crain, E.R. 1986. Log Analysis Handbook. Tulsa, Oklahoma: PennWell.
- ↑Dewan, J.T. 1983. Essentials of Modern Openhole Log Interpretation. Tulsa, Oklahoma: PennWell.
- ↑Log Interpretation Principles/Applications. 1989. Houston, Texas: Schlumberger.
- ↑Introduction to Wireline Log Analysis. 2002. Houston, Texas: Baker Hughes Inc.
- ↑Log Interpretation Charts. 2000. Sugar Land, Texas: Schlumberger.
- ↑Log Interpretation Charts. 1995. Houston, Texas: Baker Atlas, originally published by Western Atlas.
- ↑Theys, P.P. 1999. Log Data Acquisition and Quality Control, second edition. Paris, France: Editions Technip.
- ↑Fundamentals of Rock Properties. 2002. Aberdeen: Core Laboratories UK Ltd.
Noteworthy papers in OnePetro
Use this section to list papers in OnePetro that a reader who wants to learn more should definitely read
Use this section to provide links to relevant material on websites other than PetroWiki and OnePetro
Petrophysical properties of gas reservoirs
Petrophysical data sources
Petrophysical analysis case studies
AbstractFollowing the world’s first offshore production test that was conducted from a gas hydrate reservoir by a depressurization technique in 2013, the second offshore production test has been planned in the eastern Nankai Trough. In 2016, the drilling survey was performed ahead of the production test, and logging data that covers the reservoir interval were newly obtained from three wells around the test site: one well for geological survey, and two wells for monitoring surveys, during the production test. The formation evaluation using the well log data suggested that our target reservoir has a more significant heterogeneity in the gas hydrate saturation distribution than we expected, although lateral continuity of sand layers is relatively good. To evaluate the spatial distribution of gas hydrate, the integration analysis using well and seismic data was performed. The seismic amplitude analysis supports the lateral reservoir heterogeneity that has a significant positive correlation with the resistivity log data at the well locations. The spatial distribution of the apparent low-resistivity interval within the reservoir observed from log data was investigated by the P-velocity volume derived from seismic inversion. The integrated results were utilized for the pre-drill prediction of the reservoir quality at the producing wells. These approaches will reduce the risk of future commercial production from the gas hydrate reservoir. View Full-Text
Keywords: gas hydrate; reservoir heterogeneity; integration analysis; resistivity log; seismic amplitude; seismic inversion; P-velocity; second offshore production test; eastern Nankai Troughgas hydrate; reservoir heterogeneity; integration analysis; resistivity log; seismic amplitude; seismic inversion; P-velocity; second offshore production test; eastern Nankai Trough►▼ Figures
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