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Management Services

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High-Quality Geomechanical Data Prediction and Synthetic Petrophysical Logs

GEOLOG has developed a proprietary workflow named GeoMechanics that takes data from different depth-based data sets. The tests performed in different geological contexts have shown that the minimum number of wells for creating and training the Model ranges from 4 to 6 depending on the quality of the data.

  • Perform geomechanical characterization while drilling in different geological contexts (carbonates, unconventional, siliciclastic).
  • Sonic and density logs are not required in the new wells to obtain geomechanical parameters.
  • Provide an alternative to downhole tools (sonic and density) when their use is not feasible or risky.
  • Possibility to obtain the geomechanical data of existing wells in a given field to optimize future drilling.
  • Identification of potential zones of borehole instability whilst drilling, enabling timely intervention.
  • Understanding geomechanical properties to allow stimulation programs and completion to be optimized: identify zones most susceptible to fracking and indicate likely pressure requirements for successful stimulation.
  • When data sets are desirable, but conventional acquisition routes are financial or technically unattractive.


Case History

Case History

Model Building and Validation –  Offset Wells

GeoMechanics was trained with 10 wells in the same basin across carbonate formations. These wells have a full range of petrophysical well logs provided by the client (Density, Sonic and Gamma logs), and the depth-based drilling parameters and the XRF data provided by GEOLOG.

Prediction of GeoMechanical Parameters – New Wells

GeoMechanics requires depth-based drilling parameters provided by GEOLOG and gamma ray (Wireline or LWD or MWD) provided by the client. XRF can replace GR in case of data unavailability or tool failure.

Results: Poisson’s Ratio and Young’s Modulus

In the graphs the results of GeoMechanics Poisson’s ratio and Young’s Modulus. In blue, the “Conventional approach”, in red, the parameter value predicted by GEOLOG. The derived values were closely aligned with the well-log derived data for the same well with errors consistently within 5% of log values derived by conventional logs.