An experimental method to measure the porosity from cuttings: Evaluation and error analysis

As an economical approach to formation evaluation, drill cutting analysis provides significant information on petrophysical parameters which help us to understand the reservoir behavior. Researchers are gradually paying more attention to the study of drill cutting samples which potentially promote and enrich the reservoir characterization process.

This thesis project concentrates on measuring the porosity from cuttings. An evaluation of the improved method is presented by comparing porosity data estimated from artificial cuttings with various sizes to the reference value measured from core samples. Since the estimation of bulk volume is not practically possible for cutting samples, the measurement of porosity from cuttings depends on the grain volume Vg and the pore volume Vp. According to the procedure presented by IFP, the volume of grain is calculated from the weight of dried cuttings applying an average grain density. As an improved point, we will use more accurate values of grain density which obtained from conventional core analysis for measuring cuttings porosity. Additionally, the pore volume is calculated by using a saturation method adapted to cuttings.

The cuttings are obtained from crushed cores with different permeabilities and screened into four different sizes. The analysis of results shows that estimating the porosity from cuttings by using the proposed method is effective and reasonable. There is a close relationship between the results and the size of cuttings. After removing excess liquid between cuttings, the measured porosity from all cutting sizes is overestimated. Cuttings with the smallest size A (0.425-0.85 mm) show the greatest deviation. For cuttings with larger size, the measured porosity ranges smaller over time compared with that from cuttings of smaller size. We use one hour as the optimum desaturation time which corresponds to the measured results. The largest size D (2.8-4.0 mm) gave the best results that generated the minimum error. We also discussed the influence of permeability on the results.