Petrophysical data sources

In making the petrophysical calculations of lithology, net pay, porosity, water saturation, and permeability at the reservoir level, the development of a complete petrophysical database is the critical first step. This section describes the requirements for creating such a database before making any of these calculations. The topic is divided into four parts: inventory of existing petrophysical data; evaluation of the quality of existing data; conditioning the data for reservoir parameter calculations; and acquisition of additional petrophysical data, where needed. The overall goal of developing the petrophysical database is to use as much valid data as possible to develop the best standard from which to make the calculations of the petrophysical parameters.

Inventory of existing petrophysical data

To start the petrophysical calculations, the data that have been gathered previously from various wellbores throughout the reservoir must be identified, organized, and put into electronic form for future calculations.

In a typical reservoir, several "generations" of wells have been drilled. The exploration wells that discover and delineate the reservoir constitute the first generation of wells. These wells are usually drilled with scant knowledge of formation pressure, which results in deep mud-filtrate invasion in the reservoir interval for which there may be significant hole-washout problems. For this series of wells, the muds used may vary from one well to the next, and this phase may take from 1 to 10 years to complete. The second generation is the group of wells drilled during initial reservoir development. These wells are likely to be drilled with a common mud system, which might be either water-based or oil-based and will be tailored to help minimize the near-wellbore damage caused by detrimental mud-filtrate/reservoir-rock interactions. Third-generation wells may also be available. These wells would be those from later field-development activities and may have been drilled 5 to 15 years after the initial development wells were drilled.

The logs from these various generations of wells can vary in several regards. First, the logs may have been run by various service companies and may not be directly comparable to each other, even if they were from the same time period. Secondly, if the logs were run by the same service company, they may still have significant differences because different generations of logging tools were used for each set of wells. An additional difference may be between logging-while-drilling (LWD) logs and those run on wireline. LWD logging is often associated with high-angle wells. This geometry can lead to significantly different responses from zones previously seen in vertical wells and may lead to petrophysical mapping issues for high-angle-well evaluations, if not correctly accounted for.

Many of these same caveats hold for core data. The early wells may or may not have been completely cored through the reservoir interval. Later wells are more likely to be fully cored, although some zones of particular interest may have a greater concentration of cores. The routine data acquisition from cores also may vary because of different laboratories performing the core analysis on each well and because of changes in laboratory procedures and equipment over the intervening years. Also, different portions of the reservoir interval may have been analyzed with different techniques because they differ in degree of consolidation or rock heterogeneity. Special-core-analysis (SCAL) data are likely to be a variety of information because the SCAL programs for each well’s cores will be unique to the perceived data needs when each well was drilled. With respect to the geologists’ core descriptions, there may be differences between wells because different individuals prepared the various core descriptions with different techniques and emphasis. The number of petrographic measurements on cores is likely to vary widely from well to well, for example:

• Thin sections
• Scanning electron microscope (SEM)
• X-ray diffraction (XRD)]

First, the technical team must prepare several spreadsheets tabulating the basic information about each of the drilled wells. Tables 1 through 3 show templates for a spreadsheet for the log data and two for the core data, respectively. These spreadsheets provide quick access by the technical team to see what data are available, what form the data are in, how much of each type of data is available, and where gaps exist in the database. Separate sets of spreadsheets should be prepared for each of the reservoirs, if there are several separate reservoirs in a particular oil or gas field.

• 

  Table 1

• 

  Table 2

• 

  Table 3

Next, as much as possible of these detailed log and core data should be obtained in electronic form. There are a number of commercially available software packages that are useful for this purpose and can be used to access the log data and the routine-core-analysis data. However, the routine-core-analysis data may also be entered into spreadsheet form for easy use by the engineers and geoscientists. To the extent possible, the geologists’ core descriptions and petrographic measurements should be converted to electronic form for use with the other types of petrophysical data. The SCAL data will require special spreadsheet formats because each of these types of data is unique.

Core and log databases should be considered as a part of the overall reservoir database. In establishing and maintaining the overall reservoir database, controls should be in place to ensure high quality of the data and the timely inclusion of all data that are obtained.

Evaluation of the quality of existing data

The second step in working with the petrophysical data is to evaluate the quality of each of these types of data. This step requires that the data inventory and database preparation steps are completed first so that this second step can occur as a systematic and complete process. The evaluation process is a "compare and contrast" exercise.

Log data

The evaluation of log-data quality has many aspects. First, the drilling-mud and hole-condition effects may lead to no valid readings being recorded on the logs. This should be noted in the petrophysical database. "Flags" of various types should be stored, for example, to denote intervals where the hole size exceeds some limit, or where there is cycle-skipping on the sonic logs. Logging tools sometimes become temporarily stuck as a log is being run. This results in constant readings on each of the several detectors on the tool string. When the tool is stationary, each detector on it becomes stuck at a different depth, so the interval of "stuck" log will vary for each log curve. For example, the neutron log typically sticks over an interval approximately 10 ft above the stuck interval on a density log. It may be possible to "splice" in a replacement section of log from a repeated log section, or the invalid readings may simply be deleted.

Second, each log is formally calibrated before the start of each logging run by various calibration standards. The logs are also checked again after the run. Calibration records may assist in determining the quality of the logs. Perhaps of equal importance are the written comments on the log heading made immediately after the job by the logging engineer.

Third, systematic influences on the quality of log readings should be corrected. For example, if some of the wells are drilled with water-based mud (WBM), the effect of WBM-filtrate invasion on various resistivity logs can be quantified. This is done by computations made using the various resistivity logs in the same wellbore; however, where deep invasion of WBM filtrate occurs, offsetting wells drilled with oil-based mud (OBM) give a good comparison. The induction logs in OBM wells can provide accurate true reservoir resistivity values in thick hydrocarbon zones. See the resistivity and SP logging page for more information on how invasion effects can be handled. Boreholes are not always right cylinders. Holes sometimes become spiral shaped during the drilling process, and their logs show sinusoidal responses.

Routine-core analysis data

The evaluation of the quality of routine-core-analysis data starts with crossplot comparisons of various wells’ porosity, permeability, grain density, and saturation data on a reservoir or zone basis. With various wells’ data presented on the same plot one can determine if there are significantly different trends from one well to the next, for example:

• Permeability vs. porosity
• Grain density vs. porosity
• S_w vs. permeability
• S_w vs. porosity)

Differences may exist, and there may be good geologic reasons for such differences; however, some laboratory data may be of suspect quality and may require further review and inquiry.

With respect to core’s fluid-saturation data, the evaluation process must be an end-to-end review process. This evaluation begins with knowledge of the drilling mud used and whether the cores were specially cut and preserved to try to obtain undisturbed connate S_w. Second, review the core sampling and routine-core-analysis laboratory procedures to understand how those steps impacted the final fluid-saturation data reported. Well-preserved OBM cores that are analyzed using the Dean-Stark water-extraction procedure typically provide the most valid values for connate S_w in the hydrocarbon column above the mobile gas/water or oil/water transition zone. In aquifers and other mobile-water intervals, OBM-filtrate invasion displaces mobile water during core cutting, and fluid "bleeding" occurs during core surfacing. As a result, OBM-core water saturations are too low and not representative of true resident saturations. They may also be more uncertain in very poor quality, high- S w rock intervals in which it is difficult to make accurate porosity and water-volume determinations.

WBM cores can provide a qualitative measure of residual-oil saturations in the oil column after accounting for oil shrinkage and bleeding. WBM cores in oil reservoirs may also provide information about oil/water contacts (OWCs) and the S_w of low-quality rock intervals above the OWC into which oil has never entered because the entry capillary pressure, P_ce, has not been exceeded.

The OBM and WBM routine-core-analysis data should be compared and contrasted to identify how each alone, and in combination, can be used to answer certain petrophysical issues. Also, the trends of these sets of data (e.g., permeability vs. porosity) should be compared as one of the evaluation tools.

Coring in friable, uncemented, and unconsolidated sands demands special coring, handling, and analysis techniques so that the grain structure is not altered. Modern practice is to use rapid drilling rates and fiberglass or aluminum inner core barrels to minimize the friction as the core enters the barrel. The core is tripped to surface slowly and smoothly to allow dissolved gas to exit the core without disruption. The last two stands of drillpipe are the most critical because during this time the volume of gas doubles, then quadruples. During the laying down of the inner core barrel, precautions are needed to prevent bending and core deformation. For transporting the core, the inner core barrel can be cut into short (1-m/3-ft) lengths, the ends sealed with caps, then the voids between the core and the sections of the inner core barrel filled with resin. Freezing the cores in their segments before transportation is sometimes used to prevent damage, but is not very effective when there is little formation water. The costs are also higher. Cross-section X-raying of the tubes reveals which cores are damaged and which are suitable for measurements in the laboratory. See the American Petroleum Institute’s (API) RP 40 Recommended Practices for Core Analysis for details about the various types of core analysis and details of the laboratory procedures.

Special core analysis laboratory data

SCAL-data evaluation begins with a comparison of the same type of data from different laboratories and whether data from each laboratory are internally consistent. SCAL data are much more difficult to measure, and the procedures often differ from laboratory to laboratory. The challenge is to determine which of these data are more correct and should be used to make various petrophysical-parameter calculations. With SCAL data, the best approach is to have those individuals who are expert in taking and evaluating these types of data review the procedures of the various laboratories and the reported data and provide an opinion about which of these data should be used and which should be discarded.

Capillary pressure (P_c/S_w) data can be susceptible to not being taken to fully equilibrated conditions because it occasionally takes longer for equilibrium to occur than typical laboratory procedures require. This is because the relative permeability of the wetting phase becomes so low that equilibrium is very slowly reached. Additionally, the porous-plate method is susceptible to loss of capillary contact between the core plug and the porous plate. In both situations at higher capillary pressure, P_c, reported S_w values will be too high.

For the rock electrical-property laboratory measurements and how they are reported, the raw laboratory data should be reviewed very carefully to ensure that the data are of high quality and are properly reported for later S_w calculations. These measurements, as a function of brine saturation, again have the potential problem of nonequilibrium saturation distributions. Sometimes the saturation exponent, n, is a function of brine saturation, but this nonlinear behavior is typically not reported as such by the reporting laboratory. Restoration of the in-situ brine-saturation distribution is absolutely required for making laboratory rock-electrical-property and P_c measurements that lead to accurate reservoir S w calculations, so it is best if any restored-state core-plug measurements agree with similar measurements made on native-state core plugs. Finally, the resistivity index (I_R) vs. S_w data should be taken over a range of S_w values equivalent to those found in the particular reservoir. Sometimes these data are taken only down to 30% pore volume (PV) S_w, yet some of the in-situ S_w values may be in the 5 to 20% PV saturation range. If this is the case, laboratory electrical-property measurements may not lead to accurate in-situ S_w calculations from resistivity logs for the low S_w values.

Internal consistency in a laboratory’s reported results is a very good "first test" to determine if some of the data are immediately suspect. For example, if the measurements of the reduction in porosity from surface to reservoir stress vary from one set of measurements to another for a particular laboratory, then those measurements must be discarded or used very carefully. As another example, with respect to P_c/ saturation measurements, there is an immediate concern if the air/water and air/oil P_c/ saturation measurements do not reasonably overlay after accounting for the interfacial-tension (IFT) and contact angle difference between these fluid pairs. There would be a similar concern when mercury-injection P_c data are available. Again, experts in taking and using these types of data should evaluate the quality of the various sets of laboratory measurements.

Conditioning the data for reservoir parameter calculations

Conditioning the log and core data for calculations of the various petrophysical parameters includes adjustments from surface-to-reservoir conditions, normalization, and environmental-correction factors. The emphasis here is on obtaining, at reservoir conditions, a set of reliable petrophysical data that involve many wells with many sets of log data and a variety of routine and SCAL core measurements.

Log data

Each type of log data may need to be conditioned in unique ways for the subsequent petrophysical-parameter calculations. The purpose of each of these preliminary sets of calculations is to put that portion of the overall petrophysical database on a common basis.

The log data, as a whole for each well, must be depth aligned so that the various log measurements at each depth refer, as closely as possible, to the same rock volume. Differences in log response characteristics and in each tool’s path in the hole make this a complex task. Lining up the bed boundaries is particularly important. Some commercial software programs have automatic routines that perform the depth-alignment process, but, more often, shifts are made manually. Borehole-size corrections are required for most logs, while the readings of some tools require correction for other factors, such as temperature, mud density, and mud resistivity.

Histograms are often used to compare the log values of one well with the typical field values of the same log type. This process can identify logs that are miscalibrated, and it may indicate by how much they should be corrected. Bad logs that cannot be corrected by reasonable-sized shifts should be discarded from the database.

Gamma ray logs

For reservoir-wide petrophysical calculations, gamma ray (GR) logs are often normalized to reduce the variation in their values from one well to the next in intervals that are considered to have the same rock properties, usually clean sands and specific thick shale intervals.

Density and neutron logs

Log calibrations can be checked in situ because they read nearly constant values in certain formations. Anhydrite has a density value of 2.98 g/cm³ and close to zero neutron porosity, while salt has a density value of 2.04 g/cm³ and zero neutron porosity. There are few "marker" beds in which higher neutron-log readings can be verified. (See nuclear logging)

Sonic logs

Sonic logs read near-constant velocity values inside steel casing (57 μsec/ft) and in evaporate formations such as anhydrite (50 μsec/ft) and salt (67 μsec/ft). Where they occur, these constant values are used to check the correct operation of the compressional-wave travel-time tool.

Resistivity (laterolog and induction) logs

One of the main goals in developing the reservoirwide petrophysical database is to provide the most accurate true resistivity values for subsequent S_w calculations. (See the chapter on resistivity and SP logging in this section of the Handbook for information on electric logging.) Often there are several generations of laterolog and induction-logging devices that were run in the various wellbores, and this leads to a variety of data sources with different depths of investigation. Also, over the past two decades, various calculation techniques have been published to deconvolve the reported foot-by-foot resistivity values to obtain more-accurate estimates of true resistivity, R_t. Some of the more modern induction tools incorporate deconvolution into the wellsite processing.

Routine-core analysis and SCAL data

To prepare the routine-core-analysis data for use in reservoir petrophysical calculations, most of these data require adjustment from surface to reservoir conditions.

One of the first steps is aligning core data to depth-aligned log data. Frequently, a GR log of the core is measured in the laboratory, and this is used to depth match the core to the in-situ GR log. Also, in a sandstone with occasional shale intervals of low permeability, the core-analysis data must be aligned with those obvious from the downhole GR log. The log data are often digitized on a half-foot basis, but the core data are typically on a one-foot basis. As these different types of data are included in the same electronic database, care must be taken to ensure that some of the individual data points are not lost. This is likely to require a significant degree of user intervention. The core data for a particular well are really several subsets of data, each of which comes from an individual core-barrel run. These subsets of data must be kept together, and each may need to be individually depth-shifted to the log data.

Porosity data

For the routine-core-analysis porosity data, SCAL measurements of core samples’ porosity at various confining-stress levels are used as the basis for making compaction corrections. Historically, routine-core-analysis porosity measurements were taken at low stress conditions, and SCAL measurements on a small set (10 to 30) of core plugs were made to determine the relationship of porosity to overburden-stress level. Stressed-porosity values are plotted vs. laboratory stressed-porosity values to determine the relationship between the two. Regression of the porosity difference vs. surface porosity gives the same result as regressing stressed porosity vs. surface porosity. Two factors are important to consider in analyzing these plots: whether or not there is a systematic "baseline" laboratory effect related to the equipment’s coreholder tightening against the core plug at the start of the test procedure, and whether there is a systematic relationship. Theoretically, the change in porosity is a function of porosity level; however, many sets of SCAL experimental data indicate the "baseline" effect can dominate the second effect.

In the past decade, an unsteady-state style of equipment has come into fairly common usage in which routine porosity measurements can be made at both low-stress and high-stress conditions. With this equipment, reservoir-stress-level porosity measurements can be made on each and every core plug during the routine-core-analysis testing; however, typically, high-stress porosity measurements are made only on every fifth or tenth sample for later use in making the porosity adjustment from surface to reservoir conditions.

For some oil reservoirs, or OBM cores, there is a second adjustment that may need to be applied. This effect is that the routine-core-analysis procedures did not clean all of the heavy hydrocarbons from the pore space, and, hence, the measured porosity values are understated. This effect can be evaluated two ways: first, the measured grain densities may appear to be lower than expected for the particular rock type (i.e., grain densities of less than 2.65 g/cm 3 for clean sandstones); and second, if some of the routine core plugs are retested later, the cleaning solvent is found to discolor, and subsequent porosity values are found to be systematically higher than the original values. This second effect [0.5 to 1.0% bulk volume (BV)] can be as large as the stress-related porosity-reduction effect discussed in the previous paragraphs.

Permeability data

For the routine-core-analysis permeability data, SCAL measurements of core samples’ permeability at various stress levels are used as the basis for making compaction corrections. Historically, routine-core-analysis permeability measurements were taken at low-stress conditions, and SCAL measurements on a small set (10 to 30) of core plugs were made to determine the relationship of permeability to stress level. The "permeability ratio" values (stressed permeability divided by surface permeability) need to be plotted vs. surface-permeability values to determine the relationship, likely to be nonlinear, between the two. Determination of permeability at reservoir conditions is especially important in rocks with air permeabilities of less than 20 md. For low-permeability samples (<2 md), reductions in permeability of 1 to 2 orders of magnitude have been observed between values at ambient conditions and those at reservoir stress levels.

OBM water saturation data

For routine-core-analysis S w data from OBM cores, the adjustment from the surface values to those at reservoir conditions requires the application of several factors. First, the pore-volume reduction, as a result of the porosity adjustment discussed previously and because of the change in size of the core plug at stressed conditions, must be applied to the S w data. Second, the water volume and S w must be increased because of the effects of reservoir temperature and pressure, salinity, and gas in solution.

Other SCAL measurements

For other SCAL measurements, some conditioning of these data may be required. For example, for the P_c/S_w data, the data must be converted from surface to reservoir conditions and a height-above-the-OWC (H_owc) basis by accounting for the oil/water or gas/water density difference at reservoir conditions and the change in IFT and contact angle between surface and reservoir conditions.

The SCAL electrical-property measurements of a, m, and n (and possibly Q_v, a*, m*, and n*) will need to be considered in the light of the theoretical model that will be used to make S_w calculations from resistivity-log data. Many shaly-sand relationships for estimating S_w from R_t have been proposed. These parameters are sometimes measured at overburden conditions.

Other relevant data

There are various other types of wellbore data that may need to be inventoried, organized, reviewed, and considered when making the various petrophysical calculations. Other wellbore data that can be particularly important include mud-log data, formation-pressure surveys, formation-tester fluid samples, drillstem-test fluid samples, and 3D-seismic data. The Fluid contacts identification and water saturation determination pages discuss the uses of these data for the fluids-contact identification and for the S_w calculations.

Acquisition of additional petrophysical data

Often when a new petrophysical evaluation of a reservoir is undertaken, there are significant gaps in the overall database after the existing data have been inventoried and evaluated. It is possible that an acceptable petrophysical evaluation can be completed within the constraints and limitations of the available data, but sometimes additional data are needed. These new data, typically additional SCAL data or possibly routine-core-analysis data, can be obtained from two sources: additional experimental measurements on core plugs taken from existing cores; and drilling, logging, and coring new wells to obtain the needed data. The second approach is used only if such expensive data gathering is required and economically justified.

To obtain additional data from existing cores, geologists can redescribe existing cores as needed. Additional porosity and permeability measurements can be made on newly cut core plugs from any of these cores. Additional valid fluid-saturation measurements might be made on well-preserved core samples; however, such measurements have to be checked carefully because such core samples often dry out over the years. Samples can be cut for more SCAL measurements if the experts consider that the rock samples can be restored for such testing.

In some cases, the need for additional data can justify the drilling of one or more new wells in which cores are cut and routine and special logs are run. In certain equity-redetermination situations, additional wells at specific locations have been drilled to gather additional data about the reservoir interval to more accurately calculate net pay, porosity, and water saturation. For some proposed reservoir-development projects, expensive new data, often of a special nature, can be economically justified because a new well can reduce risk and improve the likelihood of project success.

Other considerations in petrophysical calculations

While we have focused on the calculation of various petrophysical properties using core and log data, there are other types of data obtained from oil and gas reservoirs that need to be considered when making petrophysical calculations. The fluid contacts identification page discusses some of these data sources, as used for determining fluid-contact depths.

Mud-log gas and oil shows

The information gathered by the mud logger regarding lithology, oil and gas shows, and gas composition should be integrated with the petrophysical calculations. In a gas reservoir, the mud log gas shows can be used to reasonably locate the gas/water contact (GWC). In an oil reservoir, this same information can be used to identify the depth of the oil/water contact (OWC). These data are useful to determine whether there is a relict-gas or -oil interval below the current GWC or OWC.

Pressure measurements and fluid samples from formation-tester logging runs

At the time wells are drilled, a suite of pressure measurements are often made over the reservoir interval, and sometimes, a few fluid samples are taken. These pressure data can aid the petrophysical interpretation by indicating whether the vertical pressures are in equilibrium throughout the reservoir interval. If not, then the reservoir may actually be several different compartments with different OWCs, GWCs, or gas/oil contacts (GOCs). The fluid samples are useful in defining which fluid is flowing in each of the tested intervals and the extent of compositional differences. In addition to pressure data, modern wireline formation-tester tools can determine hydrocarbon type, gas/oil ratio (GOR), and API gravity from spectroscopic measurements before taking fluid samples.

Drillstem-test (DST) data

The pressure and flow data from DST tests must also be considered when performing a reservoir petrophysical evaluation. These tests provide information about the flowing fluids in different portions of the reservoir. Also, the pressure-transient-analysis calculations from the flow-rate and pressure data are used to calculate an average value for reservoir permeability. This needs to be compared with that calculated from the routine-core-analysis permeability data and the well logs. The permeability values determined from these two sources of data often disagree, with the value from the DST testing almost always taken to be more correct. The DST results can be used to develop adjustments to the methodology for calculating permeability from core and log data, but also to determine the underlying technical reason for the need for the adjustments. If a DST is run long enough, it may yield information on the drainage limits of a reservoir.

Three-dimensional seismic data

The interpretation of the 3D-seismic data provides complementary data to that gathered at the wellbores and, with the rapidly improving data quality and interpretation techniques, can add significantly to reservoir-characterization calculations. The depositional, diagenetic, structural, and hydrocarbon-filling histories of a reservoir can be better understood by including the broad picture available from the 3D-seismic data. Locations of major faults that may compartmentalize the reservoir can be identified and the extent and location of channel-sand deposits is possible. Seismic attributes may be correlated with rock properties and fluid contents, allowing prediction of properties at proposed well locations.

Nomenclature

m*	=	Waxman-Smits-Thomas cementation exponent
n*	=	Waxman-Smits-Thomas saturation exponent
a*	=	Waxman-Smits cementation constant
Qv	=	cation-exchange capacity of total PV, meq/mL
Howc	=	height above the oil/water contact, L, ft [m]
Pc	=	capillary pressure, m/Lt2, psi
Rt	=	true resistivity of uninvaded, deep formation, ohm•m
Sw	=	water saturation, %PV

Noteworthy papers in OnePetro

Use this section to list papers in OnePetro that a reader who wants to learn more should definitely read

External links

Use this section to provide links to relevant material on websites other than PetroWiki and OnePetro

See also

Petrophysics

Petrophysical analysis case studies

PEH:Petrophysical_Applications

PEH:Petrophysics