Seismic attributes, petrophysical interpretation, and geostatistical modeling to enhance the development plan for a green hydrocarbon field in Mexico (Part II)

This is the second post in a series about updating the 3D geostatistical model of a green oil field. As mentioned in the previous post, the new reservoir model includes the geometric features of the sedimentary bodies identified through the analysis of the seismic attribute RMS-Amplitude (channels, lobes, sand-bars, etc.), the interpretation of pressure test results, and a fresh petrophysical interpretation of the four wells already drilled in the field. The short-term goal was to facilitate and streamline dynamic reservoir characterization, the decision-making process, and the field development planning. The cover photo and the image above are courtesy of FREEPICK.

After conducting the probabilistic analysis with multiple geostatistical realizations utilizing the 3D facies model (Base Case), a volume and maps of the Probability of SAND (PoSAND) distribution, were generated. The image below illustrates the overlay of the PoSAND contours and the seismic attribute RMS-Amplitude on top of one of the layers of interest. It's worth noting the strong correspondence between these features.

In order to increase the likelihood of the project's success, it was essential to have a strong and dependable petrophysical interpretation. Among other important factors, this interpretation needed to explicitly account for the capillary pressure effects in the reservoir, specifically the presence of multiple water levels in the reservoir column, also known as Free Water Levels (FWLs). This is crucial for accurately characterize the fluids spatial distribution and evaluate the volume of oil in this clastic reservoir.

The image below depicts the mathematical equation used in Lambda Analysis to assess Water Saturation (Sw) and the variables involved in its evaluation. As it is well known, Sw is a crucial petrophysical parameter in the characterization and oil volume calculations in clastic reservoirs; it is significantly influenced by capillary pressure effects.

Completed the above integration process, which involved analyzing seismic attributes, conducting a detailed petrophysical evaluation and interpretation, and using advanced geostatistical techniques to assess and quantify uncertainties, the final step involved comparing the already referred old model with the new one. Which model will be selected to generate recommendations and conduct fluid evaluations?

The image above displays the facies and effective porosity (PHIE) distributions for both models. The same detailed petrophysical interpretation was utilized in both cases.

It is clear that the old model, without considering the sand bodies' geometry, would lead to a significant increase in overall uncertainty. In contrast, the new model, with its inclusion of geometrical features and a reliable petrophysical interpretation, more accurately represents the uncertainties. As a result, the last provides a more realistic 3D distribution of petrophysical properties and better estimates of the oil volume than the former.

The following two images show the lateral distribution of PHIE and Oil Saturation So at the top of specific layers. Considering the results of the seismic attributes and the statistical PoSAND depicted above, it is evident that there is a correspondence and consistency among all these reservoir features.

Finally, below is a comparison of the Stock Tank Oil Initially In Place (STOIIP) volumetric statistic using both the old and new models. The old model typically overestimates the oil volume in most layers. This is expected based on the image shown above, as the old model has a tendency to distribute more sand throughout the 3D volume compared to the new model, which confines the sand to the specific sand bodies (channels, lobes, etc.).

In the first post of this series, it was mentioned that one of the proposed wells, whose trajectory was optimized using the new model, was drilled, and it yielded as much as 4000 bbl of oil per day. Further details are not provided here to maintain confidentiality...

Hoping the provided example, which showcases a successful use case of a green hydrocarbon oil field in Mexico, will be informative and help streamline processes in the oil and gas industry.

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