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Learn petrophysics by practicing with log interpretation examples


Once you have any GeolOil license (even a trial license), you may acquire our affordable server access service to an extra data set examples of fully interpreted well logs. The server access will last until the life term of your license.


Even if you regularly use another commercial petrophysical software, it is a hands-on valuable tool to understand petrophysical concepts, interpretation and computation work-flows. Learn how to compute porosity from different sources, matrix density, shaliness, mineral proportions solvers, scripting, and produce nice log displays. The data collection is continuously growing with key cases from naturally fractured reservoirs, clastic reservoirs, carbonate reservoirs, unconventional tight, and shale oil reservoirs.


Following down is a selection of some relevant processed log examples:

1. A clastic braided channels reservoir with a clay mineral solver.
2. A tight reservoir with a carbonate mineral solver and shale oil.
3. A carbonate and eolian reservoir with mineral solver and estimation of matrix density.
4. A clean eolian reservoir with indicator curve flags for net-sand and net-pay


  1. A clastic braided channels reservoir with a clay mineral solver.

    GLOG File: claySolver.glog

    This example shows how estimate the major different clay minerals of a clastic reservoir. The last two log tracks display the clay composition through the semi-quantitative technique of X-Ray diffraction, and the solution found by the GeolOil clay mineral solver. Clay discrimination is always difficult. However the mineral solved estimations, show a reasonable qualitative match against the X-Ray diffraction reference track.

    The most dominant found clay is smectite. However, around the depth MD=1820 ft., the mineral solver correctly detected the presence of the clay mineral kaolinte, which is particularly difficult to detect as its Gamma Ray response is usually low due to its low Cation Exchange Capacity. Notice on the first Lithology track, how low is the GR Gamma Ray signal compared with signal yielded by a neutron porosity minus density porosity estimator VSH. See the log plot below ↓

    Mineral solved log plot for quartz, silt, and clay minerals: illite, smectite, kaolinite, and chlorite



    The functions panel work-flow below shows all the functions and equations used, including the volume of shale VSH that was computed combining the contrast between neutron porosity and density porosity estimator, with a GR based Larionov VSH estimator:

    GeolOil full example of functions work-flow to compute clay mineral solver




  2. A tight reservoir with a carbonate mineral solver and shale oil.

    GLOG File: shaleOil.glog

    This example shows a typical work-flow to process a tight reservoir with a mineral solver for clay and carbonate minerals. Also the deeper zone has a shale oil play for which TOC Total Organic Carbon is computed using the Schmoker equation calibrated with laboratory pyrolysis data. The track Minerals shows a reasonable agreement between mineral proportions estimated by lab XRD X-Ray Diffraction, and GeolOil mineral solver ↓

    Mineral solved log plot for clays, silt, quartz, calcite, and dolomite



    The sequential functions panel work-flow below shows the steps that produce the interpretation.

    GeolOil full example of functions work-flow to interpret a tight carbonate reservoir and a shale play



  3. A carbonate and eolian reservoir with mineral solver and estimation of matrix density.

    GLOG File: RHOM1_WebExample.glog

    An accurate estimation of the matrix density RHOM ρm is a fundamental task for any petrophysicist. In complex reservoirs ρm is no longer an approximate constant value inferred from the depositional environment, but significantly varies with depth. That is ρm = ρm(depth). Once RHOM is estimated, it is used to compute porosity and water saturation —and also to estimate permeability— The brown rightmost last track "RHO matrix" on the log plot below shows how to estimate the matrix density RHOM ρm using only well log curves, without any core lab measurements available ↓

    Log plot showing the estimation of matrix density RHOM using log curves information only



    The sequential functions panel work-flow below shows the steps that produce the interpretation.

    GeolOil full example of functions work-flow to estimate matrix density RHOM



  4. A clean eolian reservoir with indicator curve flags for net-sand and net-pay

    GLOG File: wellExampleNetPay.glog

    The example below ↓ shows a log plot with indicator curve flags (GeolOil exclusive trilean logic: -1 for no, +1 for yes, 0 for inconclusive) for net-sand and net-pay. After computing cutoffs for porosity and water saturation —this eolian rock is very clean, so computation of Vshale cutoff is waved: GR here does not read clay, but remnants of organic bio-radioactivity and signal noise—, the indicator flag curves are produced with the Filtering & Upscaling module.

    GeolOil log plot of Net-Sand and Net-Pay flags


    The Upscalings Panel work-flow below ↓ shows the steps that produce the indicator curves

    GeolOil Upscaling Panel to produce net-sand and net-pay indicator flag curves







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