--> Abstract: Soft Inorganic Geochemistry: A New Concept for Unconventional Resources Modeling, by Larriestra, Claudio N.; #90163 (2013)

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Soft Inorganic Geochemistry: A New Concept for Unconventional Resources Modeling

Larriestra, Claudio N.

Soft inorganic geochemistry is defined as the spatial modeling of geochemical data which prioritizes the amount of data, their spatial relationship and their relationship with other data types (geological and geophysical data) over the individual accuracy of the chemical analyzes.

The workflow involves thousands of chemical analysis of cutting and cores samples, the processing using geostatistical techniques and the integration with well log and seismic data, to produce unconventional resources 3-D models. The workflow is made up of the following steps:

a) Non-destructive analysis of the entire samples population available, using rapid handheld X Ray Fluorescence analysis (HHXRF).
b) Selection of representative sample of entire data population (3 to 5% of data population) for destructive analysis of mineralogy (XRD) and organic geochemistry (TOC analysis).
c) Statistical analysis of the relationships between HHXRF, XRD and organic geochemistry data.
d) Integration of well log and HHXRF data using 1D Gaussian cosimulation (type II Markov model) to produce geochemical logs with an intermediate depth resolution.
e) Integration of seismic data with geochemical logs using Bayesian approach of sequential indicator simulation.

The different sources of uncertainty are the accuracy of HHXRF method, cutting sample uncertainty (provenance depth, well bore collapse and mud contamination) and the vertical seismic resolution.

The HHXRF detection variance is known because it is measured by the equipment. Uncertainty of cutting sample depth is assumed to be uniformly distributed in the sampled interval. In most cases, uncertainty of sample depth is smaller than vertical seismic resolution. Uncertainty related to cutting contamination is analyzed with the comparison of HHXRF data with chemical element background values of different rock types. Finally, the seismic data used to guide the population of inter-well space is the largest source of uncertainty.

This concept was applied to build integrated 3-D geochemical models for the D-129 and Vaca Muerta formations, both source rocks of San Jorge Gulf and Neuquén basins of Argentina. In mature oil fields with a large number of wells, this method allowed to determine source rock intervals and high brittleness zones due to rock mineralogy. Results allow to modify the stimulation method used, especially in the second case (Vaca Muerta) having high impact on overall cost and time.


AAPG Search and Discovery Article #90163©2013AAPG 2013 Annual Convention and Exhibition, Pittsburgh, Pennsylvania, May 19-22, 2013