Oil is where you find it, not always where you look for it.


Rocks, Oil, Gas, and Energy,

All of my 50+ year career has been involved with the science of Petrophysics, literally the physics of rocks, in some way or another. Petrophysics is a branch of Geoscience and intimately linked to geology, geophysics, and petroleum / mining engineering. There is no degree granted in pure petrophysics, so people in this field are often graduates of a closely related specialty and are self-taught from there.

Petrophysics is mainly used in petroleum exploitation, but also in defining mining and ground water resources.

To understand petrophysics, you need to understand rocks and the fluids they contain, how the earth's surface and subsurface change shape, and how pressure, temperature, and chemical reactions change rocks and fluids over eons of time. That's a tall order.

Rocks are formed in several ways, but usually end up as moderately flat layers, at least initially (mountain building comes later). As successive layers are laid on top of each other, the Earth builds a sequence of rocks with varying physical properties. Some layers will have open spaces, called pores or porosity, that contain fluids (water, oil, or gas). A rock on Earth with porosity cannot be "empty" -- they must contain something, even if it is only air.

Microphotograph of a rock -- black colour is the porosity where
 oil, gas, and water can be held inside the rock

Think of a porous rock as similar to a huge sponge full of holes that can soak up fluids. Although we often talk about "oil pools", these are not tanks of oil underground -- they are porous rocks. The porosity, or quantity of open space relative to the total rock volume, can range from near zero to as much as 40%. Obviously, higher values of this physical property of a rock are good news.

Some rocks have very little porosity and do not hold much in the way of fluids. These are often called "tight" rocks. Both tight and porous rocks can contain animal and plant residue that are ultimately transformed into hydrocarbons such as coal, oil, or natural gas that we can extract and use to power vehicles and heat our homes. As the plant and animal residues mature into oil or gas, they may migrate through porosity or natural fractures in the rock until trapped by a non-porous rock structure. Sometimes a rock only sources itself or an adjacent porous rock, so little migration occurs.

An anticline, the simplest form of petroleum trap

Rocks that are capable of holding  hydrocarbons in economic quantities are called reservoir rocks. Rocks in which the plant and animal residue has not been fully converted to useful hydrocarbons are called source rocks. Some rocks are both source and reservoir: others are barren of hydrocarbons, and some others may act as the trapping mechanism that keeps hydrocarbons from migrating to the surface and escaping.

A trap is what keeps oil and gas in the rocks until we drill wells to extract the hydrocarbons. Coal, being a solid, doesn't need a trap to be kept in place.

Reservoirs that contain oil or gas also contain water. The quantity of water relative to the porosity is called the water saturation. In the illustrations, the brown colour is solid rock grains and the space around the grains is the porosity. The black colour is the hydrocarbon and the white is the water, which forms a thin film coating the surfaces of each rock grain. This is a water-wet reservoir (left). In an oil-wet reservoir, the black and white colours are reversed (right).

Finding and evaluating the economics of such reservoirs is the job of teams of geoscientists and engineers in petroleum and mining companies. A petrophysicist, or someone playing this role, will be part of that team.

Once a useful accumulation has been found, drilling, completion, and production engineers take over to put wells on stream. Oil production may initially flow to surface due to the pressure in the reservoir. Some oil pools do not have enough pressure to do this and need to be pumped. Depending on the reservoir drive mechanism, some wells that start flowing will later need to be pumped. Water may be produced with the oil. It is separated and disposed of by re-injection into a nearby unproductive reservoir layer. You can't just dump the water in the nearest swamp.


   Aquifer Drive -- Before ... and After some production            Gas Cap Drive               Gas Expansion Drive

An aquifer drive mechanism usually maintains the reservoir pressure for some time but may drop off gradually. Recovery factors vary from 30 to 80% of the oil in place. The oil water contact rises as production depletes the oil. A gas cap drive pushes oil out as the gas expands. Recovery factor is similar to aquifer drive. There may or may not be some aquifer support. the gas oil contact drops as the oil is depleted. Gas expansion reservoirs do not have aquifer or gas cap support. Gas dissolved in the oil expels oil into the well bore because the pressure at the well bore is below the reservoir pressure. Recovery factor is awful - usually less than 10%, but this can be improved to maybe 20% by injecting water nearby to increase or maintain the reservoir pressure. Water floods, carbon dioxide injection, and re-injection of produced gas or water can be used in nearly any reservoir to improve recovery efficiency.

Gas wells do not need pumps, but if they also produce water, a special process called artificial lift is used to get the water out. That water is also disposed of legally.

The economics of a reservoir varies with improving technology. Bypassed reservoirs, discovered and ignored years ago, are now economic due to technical improvements in drilling practices and reservoir stimulation techniques. Horizontal wells and deep water drilling are now common. The use of heat or steam to assist production of heavy oil or bitumen, and multi-stage hydraulic fracturing to stimulate production in tighter reservoirs are relatively new techniques and relatively economic today. Obviously the specific price of oil or gas after delivery to the customer plays an important role in how much effort can be expended to recover oil and gas from underground.

There is controversy, of course, about new technology. Just as the Luddites resisted the weaving machines in the early 1800's, modern Luddites insist that the old ways of oil and gas extraction are best, while at the same time complaining loudly about the price of gasoline at the pumps or the cost of electricity for their air conditioners. You can't have low-cost and low-tech at the same time.

Green alternatives are 50 to 100 years away. Every green technology needs oil to make the required plastics and fuel the manufacturing and delivery systems. The electricity grid is far too fragile to fuel extensive use of electric vehicles anywhere, let alone everywhere. And where would all that electricity come from (coal?). Clean coal is more oxymoronic than military intelligence. So if you and the other 7 Billion people on this planet want to live a comfortable life, get used to oil and its risks. Staying in bed is risky too -- more people die in bed than anywhere else.

For the record, I've been off the grid with wind or solar since 1984. But I live in the middle of nowhere so the esthetics don't bother the neighbours. What have you done to green-up this world?

"Last week, I couldn't spell Petrophysicist. Now I are one." That describes me in 1962 as I moved from Montreal to Red Deer, Alberta to run well logs for a company called Schlumberger. The word petrophysics had been coined 20 years earlier by a geologist named Gus Archie and it wasn't used much back in the day. Lately it has attained a certain cachet, denoting a professional level career path.

What is a "well log" you ask. It is a record of measurements of physical properties of rocks taken in a well bore, usually drilled for oil or gas, but possibly for ground water or minerals. Think of a ship's log. The first record of such a log dates back to 1846 when Lord Kelvin measured temperature versus depth in water wells in England, from which he deduced that the Earth was 7000 years old. The fact that he was wrong is not important. Log analysis is an imperfect science.

Illustration of a wireline logging job: logging truck with computer cabin, cable and winch (right), cable strung from winch into drilling rig derrick and lowered into bore hole, with logging tool at the end of the cable. Logs are recording while pulling the tool up the hole. Logs can also be run with special tools located at the bottom of the drilling string, or conventional tools can be conveyed on coiled tubing or drill pipe

The first logs for oil field investigation were run by the Schlumberger brothers, Marcel and Conrad,  in 1928 in Pechebron, France. Soon, the service migrated to North and South America, Russia, and other locations in Asia. At that time, the only measurement that could be made was of the electrical resistivity of the rocks. High resistivity meant porous rock with oil or gas, or porous rock with fresh water, or tight rock with very low porosity. Low resistivity meant porous rock with salty water or shale. Take your pick. Local knowledge helped.

One virtue of the well log was that the top and bottom of each rock layer could be defined quite accurately. When the log and depths were compared to the rock sample chips created by the drilling process, a reasonable geological interpretation might be possible, but was far from infallible. 

By 1932, the spontaneous potential (SP) measurement was added. The analysis rules expanded: low SP meant shale, or tight rock, or fresh water. High values meant salt water with or without oil or gas in a porous rock. The resistivity could then be used to decide on water versus hydrocarbons. Perfect. Except there were lots of shades of grey and the SP was not always capable of defining anything.

s from 1932 in Oil City-Titusville area, Pennsylvania, the location of Edwin Drake's "First Oil Well" (in the USA - 6 other countries had oil wells predating this one). His well was only 69 feet deep, so it penetrated just to the top of these logs, which found deeper and more prolific reservoirs. Each pair of curves represents the measured data versus depth for one well. The SP is the left hand curve of each pair; deflections to the left (shaded) show porous rock. The resistivity is the curve on the right of each pair. Deflections to the right (shaded) show high resistivity, and when combined with a good SP deflection, indicate oil zones. Some good quality rocks in this example do not have high resistivity and are most likely water bearing.

The gamma ray log appeared in 1936. The rules were easy: low value equaled porous reservoir or tight rocks. High values were shale. It said nothing about fluid content.

By 1942, Gus Archie had defined a couple of quantitative methods that turned analysis into a mathematical game, instead of just some simple rules of thumb. His major work established a relationship between resistivity, water saturation, and porosity. If we knew porosity from rock samples measured in the lab, and a few other parameters, we could calculate water saturation from the resistivity log values. This was really new news.

He even attempted to calculate porosity from the resistivity log. This worked in high quality (high porosity) reservoirs but had problems in low quality rocks or heavy oil.

Just after 1945, a method that investigated the response of rocks to neutron bombardment became available. The neutron log was the first porosity indicating well log. High values meant low porosity or high porosity with gas. Low values meant high porosity with oil or water, or shale. Add the gamma ray log, SP, and resistivity and again the world was perfect, except for all those shades of grey. Calibrating the response to porosity depended on a lot of well bore environmental parameters (hole size, mud weight, temperature) so it was not terribly accurate.

It wasn't until 1958 that the measurement of the velocity (or travel time) of sound through rocks in a well bore was achieved. It turned out that the travel time was a linear function of porosity and a few other factors.


This is an example of a modern sonic log with gamma ray and caliper curves (far left), shear and compressional sonic travel time curves (middle) and sonic waveform image log (right). Depths are shown in the narrow track next to the gamma ray curve.

Shortly after 1960, another porosity indicating log appeared that measured the apparent density of the rocks. Porosity was a linear function of density -- higher density meant lower porosity.


Both sonic travel time and density as measured by these logs could be transformed into moderately accurate porosity values, using the gamma ray to discount shale, and the resistivity to distinguish between salty water and oil. Fresh water was still a problem and gas zones could only be located if a neutron log was also run.

This was the state of petrophysics when I entered the scene in 1962. The rules were obvious, the math was easy. And running the logging tools into the well bore meant lots of travel. I loved the job. There were no computers on every desk, calculators were bigger and heavier than typewriters, so the quantitative work was done with penciland paper or sliderule. Anybody know what a sliderule is?

Later, with sidetracks into seismic data processing, reservoir engineering, project management, and seismic data center management, I finally noticed that petrophysics was the underlying foundation of much of geology, geophysics, and reservoir engineering.

That realization led me to my consulting and teaching career. I got to see a lot of the world, wrote a dozen or more software packages, analyzed the log data from thousands of wells, and saw even more more of the world,


This may be the only editorial cartoon ever published in a newspaper (Calgary Herald, circa 1974 - 75) concerning petrophysical analysis. That`s me peering down a borehole on Melville Island NWT, estimating the gas reserves to be "four trillion cubic feet". The final value was closer to 17 trillion. I was the log analyst and logging supervisor on about 140 wells in the Canadian Arctic across a 10 year period. We didn`t use our eyeballs to look into the wellbores directly, of course; we used well logs and calcualtions based on those measurements
to do what our eyes could not.


Mainframe computers and dumb terminals were really unfriendly environments. It was apparent that some portable form of computer was needed to do the math and make pretty images of our results to show to management and team members. Five years before the IBM-PC, the HP9825 calculator became a computer and LOG/MATE, "The Friendly Log Analysis System", was born (1976). Today, far more sophisticated and powrerful systems are commont, but LOG/MATE was the first.

Adverisemenys for my two major forays into the software business: LOG/MATE 1976 (left), META/LOG (1986)

We now call the business "Integrated Petrophysics" because we use much more than log data to get our answers. Lab data from core analysis, such as porosity, permeability and grain density, are critical input parameters used to calibrate our work. More exotic lab measurements have become more common as we move into unconventional reservoir types like shale gas and tight oil prospects.

The table below might not mean too much to someone who is not in the oil and gas business, but it will give everyone an idea of the scope of work, wealth of data types, and the multiplicity of uses that petrophysical data  can be applied to.

DATA USES -  General Outline
    Petrophysical Analysis
    Geophysical Applications
    Geological Applications
    Drilling Applications
    Engineering Applications
    Completion Applications
    Production Applications

DATA USES - Petrophysical Analysis
    Shale Content
    Water Saturation
    Movable Hydrocarbon
    Irreducible Water Saturation
    Water Cut / Relative Permeability
    Permeability / Productivity
    Fracture Intensity / Orientation
    Fluid Contacts - Original and Dated
    Productive Intervals
    Swept Zones
    Pore Volume / Hydrocarbon Pore Volume
    Flow Capacity
    "Net Pay"

    Where Are The Reserves?
    How Much Does This Well Contribute?

DATA USES - Geophysical Applications

    Velocity and Density
    Seismic Modelling
    Synthetic Seismograms
    Editing Logs for Seismic
       Bad Hole Condition
       Missing Log Data
    Modeling Hypothetical Rock Sequences
    Modeling Hypothetical Fluid Content
    Vertical Seismic Profiles
    Seismic While Drilling
    Calibrating Seismic Inversion
    Calibrating Seismic Attributes
    Amplitude versus Offset Models

    Is the Seismic Interpretation Realistic?

DATA USES - Geological Applications

    Reservoir Description
    Structure and Stratigraphy
    Dip and Direction
    Sedimentary Models
    Sequence Stratigraphy
    Bedding Type / Orientation
    Depositional Environment

    Tectonic Structures
    Sedimentary Structures
    Multi-well Analysis
    Cross Sections / Fence Diagrams
    3-D Visualization
    Correlation and Mapping

    What Are the Geologic Risks?

DATA USES - Drilling Applications

    Designing Vertical Wells
    Designing Deviated Wells
    Designing Horizontal Wells
    Drilling Prognosis
    Stress Regimes / Fractures
    Borehole Stability
    Bit Selection
    Cost Estimates

    Where Are The Drilling Risks?

DATA USES - Engineering Applications

    Calculating Reserves
    Calculating Productivity
    Calculating Cash Flow
    Reservoir Simulation / Modeling
    History Matching
    Production Prediction
    Production Optimization
    Economic Analysis

    Is The Well/Pool/Project Any Good? 

DATA USES - Completion Applications

    Perforating Interval
    Stress Regime / Orientation
    Hydraulic Fracture Design
    Acidizing / Other Treatments
    Sand Control
    Maximize Productivity
    Are There More Targets?

    Is production maximized?

DATA USES - Production Applications

    Through Casing Reservoir Description
    Fluid Identification
    Cement Evaluation
    Casing Inspection
    Flow and Production Analysis
    Gas Leak Detection

    How Do We Repair The Well?

DATA TYPES ­ General Outline
    Air / Satellite Images

    Well History
       Tops, Tests, Cores, Perfs, Logs, Status
    Logs - Many Variations
    Cores - Many Types of Analyses
    Data Gathering Considerations
    Data Digitizing
    Project Planning
    Quality Control


    Fluid Properties
    Pressure Transient
    Wellhead / Bottomhole Pressures
    Production History
    Injection History
    Completion Diagram
    Facilities In Place / Needed
    Economics / Costs / Prices

DATA TYPES ­ While Drilling
    Sample Descriptions
    Drilling Records
    Mud Logs
    Core Descriptions
    Measurements While Drilling
    Logging While Drilling
    Seismic While Drilling

DATA TYPES ­ After Drilling
    Conventional Open Hole Logs
    Image Logs
    Thin Bed Tools and Processing
    Petrophysical Analysis Results
    Geological Correlations / Maps
    Seismic Analysis / VSP
    Test Results
    Core Analysis Results

DATA TYPES - Open Hole Logs

    Resistivity and Resistivity Imaging
    Acoustic and Full Wave Acoustic
    Natural and Spectral Gamma Ray
    Formation Density and Litho Density
    Neutron Porosity
    Dipmeter and Deviation Surveys
    Formation Imager and Televiewer
    Nuclear Magnetic Resonance
    Induced Gamma Ray Spectroscopy
    Pulsed Neutron and Activation
    Pressure Profiles / Sample Taker
    Sidewall Cores

DATA TYPES ­ After Completion

    Cased Hole Logging
    Reservoir Description Logs
    Production Logs
    Casing / Cement Evaluation Logs
    Bottom Hole Pressure Survey
    Well Test Results
    Initial Production / AOF / IPR

DATA TYPES ­ Special Cases

    Horizontal / Deviated Wells
    Logging Through Drill Pipe
    Coiled Tubing Logging

DATA TYPES ­ Core Data

    Conventional Core Analysis
       Permeability, Porosity, Saturation
       Grain Density Lithology Description
    Special Core Analysis
       Electrical Properties
       Capillary Pressure
       Relative Permeability
       Thin Section Petrography
       Scanning Electron Micrographs
       X-Ray Diffraction
       Infra-red Mineralogy
    Core Imaging
       White Light
       Ultra Violet Light
       CT Scans

DATA TYPES ­ Fluid Properties

    Density, Viscosity
    Water Resistivity, Chemical Analysis
    Oil / Gas Analyses

DATA TYPES ­ Pressure Transient

    Pressure versus Time
    Buildup or Drawdown
    Horner / Ramey Plots
    PBU Modeling / Curve Fitting
    Static Wellhead Pressure
    Static Bottom Hole Pressure

DATA TYPES ­ Production Data

    Oil / Gas / Water Rates
    Changes With Time
    Completion History
    Well / Pool / Reservoir Summaries
    Deliverability Analysis Results


I have been teaching the practical application of petrophysics since 1967. The seminars always start with "What is a log?" and "What do we do with them?". The first question was answered in the previous section. Here, I'll try to provide an answer to the second, just as it s done in the seminar. We use the rules as developed over the last 80 years and apply them to the individual log curves as we see them on paper or on a computer screen.

The step by step procedure using Crain's Rules will reduce the complexcity considerably and give you a straight forward path toward your goal. The illustration below is to give you a few of the basic rules in one single illustration. Further on there is a more detailed coverage of the Rules.


Lets start with just 3 curves - the gamma ray (GR), resistivity, and a porosity indicating log (a sonic in this example). The GR is at the far left and the sonic is the left edge of the red shading. The resistivity and sonic have been overlaid to make it easier to see the shape of the two curves relative to each other.


Basic Rule "A": When GR (or SP) deflect to the left the zone is clean and might be a reservoir quality rock. When GR deflects to the right, the zone is usually shale (not a reservoir quality rock). There are exceptions to this rule, of course.


Basic Rule "B": Porosity logs are scaled to show higher porosity to the left and lower porosity to the right. Clean and porous is good, so compare the GR to the porosity log and mark clean+porous zones.


Basic Rule "C": Resistivity logs are scaled to show higher resistivity toward the right. Higher resistivities mean hydrocarbons or low porosity. Low resistivity means shale or water zones. So clean+porous+high resistivity are good. There are exceptions to this rule too.


The exceptions are what makes the job interesting. There are low resistivity pay zones, radioactive (high GR) pay zones, gas shales, oil shales, coal bed methane, and low porosity zones that produce for years. Some of these are shown in the illustration. See if you can figure out the logic behind each of the interpretations shown here before you move on to the more formal rules.


The more detailed Crain's Rules are described here with reference to the logs shown below.


Crain’s Rule “Minus 1”: Identify log curves available, and determine their scales.

The left half of this image shows a resistivity log with spontaneous potential (SP) in Track 1 and shallow, medium, and deep resistivity (RESS, RESM, RESD) on a logarithmic track to the right of the depth track. The right half of the image shows a density neutron log with gamma ray (GR) and caliper (CAL) in Track 1. Photo electric effect (PE) is in Track 2 with neutron porosity (PHIN) and density porosity (PHID) spread across
Tracks 2 and 3.

Crain’s Rule #0: Gamma ray or SP deflections to the left indicate cleaner sands, deflections to the right are shaly. "Shay Sands" fall in between these two extremes. Draw clean and shale lines, then interpolate linearly between clean and shale lines to visually estimate Shale Volume (Vsh).

To find clean zones versus shale zones, examine the spontaneous potential (SP) response, gamma ray (GR) response, and density neutron separation. Low values of GR, highly negative values of SP, or density neutron curves falling close to each other usually indicate low shale volume. High GR values, no SP deflection, or large separation on density neutron curves normally indicate high shale volume.


Very shaly beds are not “Zones of Interest”. Everything else, including shaly sands (Vsh < 0.50) and even obvious water zones, are interesting. Although a zone may be water bearing, it is still a useful source of log analysis information, and is still a zone of interest at this stage.


Crain’s Rule #1: The average of density and neutron porosity in a clean zone (regardless of mineralogy) is a good first estimate for Effective Porosity (PHIe).


Crain’s Rule #2: The density porosity in a shaly sand is a good first estimate for Effective Porosity (PHIe), provided logs are on "Sandstone Units" scale.


For zones of interest, draw bed boundaries (horizontal lines). Then review the porosity logs: sonic, density, and neutron. All porosity logs deflect to the left for increased porosity. If density neutron data is available, estimate porosity in clean sands by averaging the two log values. In shaly sands, read the density porosity.
 IMPORTANT: This is just an estimate and not a final answer -- computer programs will do the work more accurately, especia;;y pn shaly sands. accurately.


Scale the sonic log based on the assumed matrix lithology. Mark coal and salt beds, which appear to have very high porosity -- they don't; it is just an artifact of the log scale combined with their unique petrophysical properties. Identify zones which show high medium, low, or no porosity. Low porosity, high shale content, coal, and salt beds are no longer “interesting” as conventional reservoirs.


Crain’s Rule #3: Tracking of porosity with resistivity on an overlay usually indicates water or shale.


Low resistivity with moderate to high porosity usually indicates water or shale.

Crain’s Rule #4: Crossover of porosity on a resistivity--porosity overlay usually indicates hydrocarbons.


High resistivity with moderate to high porosity usually indicates hydrocarbons.



Raw logs showing resistivity--porosity overlay. Red shading indicates possible hydrocarbon zones. The density or density porosity (solid red curve) is placed on top of the deep resistivity curve (dashed red curve). Line up the two curves so that they lie on top of each other in obvious water zones. If there are no obvious water zones, line them up in the shale zones. If the porosity curve falls to the LEFT of the resistivity curve, as in Layers A and B, hydrocarbons are probably present.


To find hydrocarbon indications and obvious water zones, compare deep resistivity to porosity, by mentally or physically overlaying the density porosity on top of the resistivity log. High porosity (deflections on the density log to the left) and high resistivity (deflections to the right) usually indicate oil or gas, or fresh water. See red shaded area on resistivity track on the log above.


Layer A above is a shaly sand and has medium porosity. Layers B and C are clean sands and have high porosity. All other layers are shale with no useful porosity.


The average of density and neutron porosity in Layers B is 24 %; Layer C is 19%. This is close to the final answer because there is not much shale in these zones. The average in Layer A is 16 % - much higher than the truth due to the influence of the shale in the shaly sand. The density porosity is about 11%, pretty close to the core data. Therefore all our analysis must make use of shale correction methods. Crain's Rule #1 handles visual analysis of clean sands (up to about 25% shale) and Crain's Rule #2 handles shaly sands.


Low resistivity and high porosity usually means water, as in Layer C. Known DST, production, or mud log indications of oil or gas are helpful indicators.


Layer B and Layer A show crossover when the porosity is traced on the resistivity log, so these zones remain interesting. In fresher water formations, it is often difficult or impossible to spot hydrocarbons visually. If it was easy, log analysts would be out of work!


Crossover on the density neutron log sometimes means gas (not seen on the above example). Watch for rough hole problems, sandstone recorded on a limestone scale, or limestone recorded on a dolomite scale, which can also show crossover – not caused by gas.


Water zones with high porosity and low resistivity are called “obvious water zones”. Fresh water may look like hydrocarbons, particularly in shallow zones. The lack of SP development will often help distinguish fresh water zones. Low porosity water zones may not be obvious.



Crain’s Rule #5: Approximate Water Saturation (SWa) in an obvious hydrocarbon zone is estimated from:  SWa = Constant / PHIe / (1 - Vsh)

where Constant is in the range from 0.0100 to 0.1200.
Use 0.0400 as a first try in sands, 0.0600 to 0.0800 in shaly sands, and 0.0250 in intercrystalline carbonates.


In computer programs, w
ater saturation is usually calculated from the Archie equation or a shale corrected version of it. This is not easy to do with mental arithmetic. An easier estimate of water saturation Crain's Rule # 5: In obvious hydrocarbon zones use a method attributed to Buckles, SWa = Constant /PHIe. In obvious water zones, SWa = 1.00. If it is not obvious, get professional advice.


Here is the computer output from the data in the logs used in the visual analysis shown above.


This depth plot is typical of a straight forward petrophysical analysis. Some raw data curves are presented because most people find them helpful in correlating the zones of interest. From left to right are gamma ray (GR), spontaneous potential (SP), then three different resistivity curves (RESD, RESM, RESS) with the depth numbers in between them and the GR / SP track.


Next come some answers, from left to right, water saturation (SW), porosity (PHIe), permeability (Perm), and the mineral breakdown on the right. This latter track shows only shale and quartz in this example.


The solid red shading in the porosity track is the oil in the porosity. More red is good news. The white area to the right of the oil is the water volume in the reservoir.


Using the curve colour codes and scales at the top of the log, you can identify each curve and read values for the answers. For example the upper oil zone has about 10% porosity, 40% water saturation. The zone is 50-60% shale with the balance being quartz.


The lower oil zone has 24% porosity, 17% water saturation, nearly zero shale. The white area underneath the red, indicates a watrer zone under the oil zone.


Coloured dots represent lab analysis data for [orosity and permeability. The close agreement with the log analysis means we did a good job. This may have taken a few iterations to get all the parameters just right.




The mineral makeup of the rocks can often be determined if the petrophysicist becomes familiar with a few more rules, and can memorize some numerical values that represent individual minerals.



Crain’s Rule #6: On Limestone Units logs, the density neutron separation for limestone is near zero, dolomite is 8 to 12 porosity units, and anhydrite is 15 or more. Sandstone has up to 7 porosity units crossover.


On Sandstone Units logs, separation for sandstone is near zero, limestone is about 7 porosity units, dolomite is 15 or more, and anhydrite is 22 or more.



Visual determination of lithology (in addition to identifying shale as discussed earlier) is done by noting the quantity of density neutron separation and/or by noting absolute values of the photo electric curve. The rules take a little memory work.


You must know whether the density neutron log is recorded on Sandstone, Limestone, or Dolomite porosity scales, before you apply Crain’s Rule #5. The porosity scale on the log is a function of choices made at the time of logging and have nothing to do with the rocks being logged. Ideally, sand-shale sequences are logged on Sandstone scales and carbonate sequences on Limestone scales. The real world is far from ideal, so you could find any porosity scale in any rock sequence. Take care!



 Sand – shale identification from gamma ray and density-neutron separation. Small amounts of density neutron separation with a low gamma ray may indicate some heavy minerals in a sandstone. Most minerals are heavier than quartz, so any cementing materials, volcanic rock fragments, or mica will cause some separation.  Both pure quartz (no separation) and quartz with heavy minerals (some separation) are seen.



 Lithology identification is accomplished by observation of density neutron separation and the gamma ray response, along with a review of core and sample descriptions.


The photoelectric effect is often a direct  mineralogy indicator.


Crain’s Rule #7: PE below 1 is coal, near 2 is sandstone, near 3 is dolomite or shale, and near 5 is limestone or anhydrite. The high density (negative density porosity) of anhydrite will distinguish anhydrite from limestone. High gamma ray will distinguish shale from dolomite.




ROCK   N–D   N–D   PE   GR
            (SS)   (LS)
SAND      0     --7     2    LO
LIME       7       0     5    LO
DOLO   15+      8+   3    LO
ANHY    22+    15+   5    LO
SALT  --37     --45   4.5   LO
SHLE    20+     13+ 3.5   HI

Memorize this table, or keep a copy in your wallet. Practice the skill and use it in your daily work.

1. Find the evidence
2. Assess the evidence
3. Postulate all possibilities
4. Eliminate the impossible
5: Select the answer that fits best with the evidence

Remember: logs are not perfect and these rules are not perfect. Adjust the rules to suit your experience. Mineral mixtures are common, so think in terms of what is possible in each case.

On the log at the right, the evidence and conclusion is shown for 6 layers with different lithology.

This is a LIMESTONE scale log


RULE EXCEPTIONS: High GR log readings coupled with density neutron log readings that are close together, are a sign of radioactive sandstone or limestone. To tell radioactive dolomite zones from shale zones, use a gamma ray spectral log, since the density neutron log will show separation in both cases. The PE value can help differentiate between radioactive dolomite and chlorite shale but not between dolomite and illite rich shale. High thorium values on the gamma ray spectral log indicate the shale.



Crain’s Rule #8: If it is porous, it is probably permeable. A quicklook equation for permeability in intergranular or intercrystalline porosity is: Perm = 100 000 * (PHIe^6) / (Sw^2).


To find signs of permeability, look for indications of porosity, mudcake shown by the caliper, separation on the resistivity log curves, known production or tested intervals, sample descriptions, and hydrocarbon shows in the mud.


A quicklook equation for permeability is:
     Perm in milliDarcies = 100 000 * (Porosity ^ 6) / (Water Saturation ^ 2)


Crain’s Rule #9: If the logs are noisy, blame it on fractures.


To check for indications of fractures, look for sonic log skips, density neutron crossover in carbonates, hashy dipmeter curves, hashy resistivity curves, or caved hole in carbonates.


Crain’s Rule #10: Check your work and revise your assumptions, then refine rules for each project.


When lab data is available, checking the answers is relatively easy. If the match between the log analysis results and lab data is poor, then some parameters in the analyis model need to be refined. That's where the "Art of Petrophysics" takes over from the "Science of Petrophysics". Below is an exaample of the core data (coloured dots) matching the log data, or vice versa.

“Tight Oil” example showing raw log data on left half of image and petrophysical properties (answers) derived from that data on the right half. Raw data includes (from left to right) gamma ray, caliper, shallow and deep resistivity, photo electric effect, neutron porosity, density porosity, and sonic travel time. In this example, high resistivity represents organic rich source rock (shale) and lower values are found in the oil zone. The answers are (from left to right) porosity, oil volume in porosity (shaded red), water volume in porosity (shaded white), water saturation, permeability, and mineralogy (various colour symbols) at right of image. Core porosity (black dots), core oil saturation (red dots). core water saturation (blue dots), and core permeability (red dots) are plotted on the log analysis results to demonstrate how well the mathematical model matches ground truth. The model and parameters can then be used on other wells that do not have this type of control data. My first colour plot, considerably less elaborate than this one, was generated from my own software-hardware package (LOG/MATE) in 1976 from a minicomputer with only 8 Kb RAM. IBM didn't "invent" the PC until 1981.