COMPARISON AND PREDICTION OF HIGH-RESOLUTION PROBE SCREENING MEASUREMENTS ON ROCK CORES
Creators: Okwoli, Emmanuel
Publisher: name: University of Alberta Library
Year: 2023

<p>Traditional routine core analysis typically involves studying cylindrical core plug samples (1 inch diameter and 1.5 inches long) that are cut every 1 foot along the whole core. This thesis compares a range of novel probe screening measurements on slabbed core that provide a rapid, high-resolution, less destructive and cost-effective means of characterizing variations of petrophysical parameters in heterogeneous reservoirs compared to traditional analysis on core plugs. Detailed comparisons of probe measurements from two large datasets on slabbed core were performed. Dataset 1 contained high-resolution probe permeability, probe acoustics (from which probe porosity was also generated) and probe luminance (from linear X-ray) measurements on slabbed core from some North Sea oil reservoirs. Dataset 2 contained probe magnetic susceptibility and probe X-ray fluorescence measurements on slabbed core from some oil sands wells in Alberta. The main aims of the study were firstly to identify correlations between the various probe parameter measurements in each dataset, and secondly to predict and verify probe parameter values (permeability, acoustics and luminance in Dataset 1, and elemental contents in Dataset 2) at high-resolution using combinations of the other measured probe values or using well log data. <br>
Different numerical methods were adopted to compare the probe results and create predictions and verifications. Linear regression and multiple linear regression methods were initially used to determine any correlations between the diverse probe measurements and make predictions. The regression results showed some relatively strong correlations between the different probe parameters (particularly for smoothed data), suggesting the potential of using any one (or a combination) of the parameters to predict the high-resolution profiles of any of the other parameters. Subsequently, non-linear methods including backpropagation artificial neural networks (BP-ANNs) and two-dimensional convolutional neural networks (2D CNNs) were adopted to improve the predictions.  Both the ANNs and 2D CNNs produced excellent correlations between the predicted and measured values for the different cases considered, with many results exhibiting a perfect correlation with a regression coefficient of determination (R2 value) of 1.00. In Dataset 2 the 2D CNN predictors marginally outperformed the ANNs in some cases.<br>
Low field mass magnetic susceptibility measurements on core plugs from Dataset 1 were also correlated with core plug permeability data. Negative magnetic susceptibility values corresponded with high permeability values (&gt;100 mD), whereas positive magnetic susceptibility values corresponded with low permeability values (&lt;100 mD). Moreover, the raw magnetic susceptibility values were processed to give illite contents, which correlated with permeability values. Although we didn’t have a probe magnetic susceptibility sensor when the Dataset 1 slabbed core was available, the core plug results suggested the potential of probe magnetic susceptibility for rapid, high-resolution permeability and mineral content prediction for the slabbed core of Dataset 1. <br>
The novel probe techniques described in this thesis provide cheap, environmentally friendly “quick look” petrophysical appraisals, which are not only relevant for hydrocarbon exploration, but also for reservoirs associated with energy transition. For these latter reservoirs, it is crucial to have a high-resolution continuous record of petrophysical properties so that key features are not missed (e.g., seals and fractures that may be important for CO2 or H2 storage applications).</p>