Integrated Work Flow Delivers Precise Properties Input for Unconventional Simulation

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 203374, “Is My Completions Engineer Provided With the Correct Petrophysical and Geomechanical Properties Inputs?” by Philippe Gaillot, Brian Crawford, and Yueming Liang, SPE, ExxonMobil, et al., prepared for the 2020 Abu Dhabi International Petroleum Exhibition and Conference, Abu Dhabi, held virtually 9–12 November. The paper has not been peer reviewed. To simulate the performance of unconventional wells effectively, incorporating sufficient geological complexity is essential to allow for realistic variability in the petrophysical and mechanical properties controlling the productivity of the effective stimulated rock volume (ESRV). The complete paper presents an integrated work flow to model mechanical properties at sufficiently high resolution (centimeter scale) to accurately honor rock fabric and its height and complexity effects on hydraulic fracturing and, therefore, on production. Once upscaled, outputs of this work flow enable a more-realistic borehole view of reservoir quality, fluid-flow units, and geomechanical stratigraphy, all information key to optimal asset development. Introduction Simulating hydraulic fractures with pre-existing natural mechanical discontinuities remains an important challenge. In most cases, the trend is to include more details in the simulations and apply more computational power to solve the problem. While these complex numerical simulations allow simultaneous interaction between multiple phenomena, the validity of the predicted hydraulic fractures, and thus ESRV productivity, may be questionable if inputs to the hydraulic-fracturing and production models do not capture the effective fine-scale complexity of the formation properties, namely the minimum in-situ horizontal stress contrast between layers, the changing layer properties, and the mechanical and flow properties of the interfaces. The complete paper presents a seven-step work flow wherein core poroelastic anisotropies derived from quantitative mineralogy and well-established micro-mechanical theory are integrated into a high-vertical-resolution multiphysics petrophysical model able to capture the centimeter-scale level of heterogeneity observed from cores. The resulting high-vertical-resolution well frame-work enables a detailed well-scale calibration and recognition of facies and stacking patterns; an accurate and core-calibrated geochemical, petrophysical, and geomechanical characterization of individual beds; and an identification and characterization of the interfaces between beds.

Monitoring of Lithium Contents in Lithium Ores and Concentrate-Assessment Using X-ray Diffraction (XRD)

Lithium plays an increasing role in battery applications, but is also used in ceramics and other chemical applications. Therefore, a higher demand can be expected for the coming years. Lithium occurs in nature mainly in different mineralizations but also in large salt lakes in dry areas. As lithium cannot normally be analyzed using XRF-techniques (XRF = X-ray Fluorescence), the element must be analyzed by time consuming wet chemical treatment techniques. This paper concentrates on XRD techniques for the quantitative analysis of lithium minerals and the resulting recalculation using additional statistical methods of the lithium contents. Many lithium containing ores and concentrates are rather simple in mineralogical composition and are often based on binary mineral assemblages. Using these compositions in binary and ternary mixtures of lithium minerals, such as spodumene, amblygonite, lepidolite, zinnwaldite, petalite and triphylite, a quantification of mineral content can be made. The recalculation of lithium content from quantitative mineralogical analysis leads to a fast and reliable lithium determination in the ores and concentrates. The techniques used for the characterization were quantitative mineralogy by the Rietveld method for determining the quantitative mineral compositions and statistical calculations using additional methods such as partial least square regression (PLSR) and cluster analysis methods to predict additional parameters, like quality, of the samples. The statistical calculations and calibration techniques makes it especially possible to quantify reliable and fast. Samples and concentrates from different lithium deposits and occurrences around the world were used for these investigations. Using the proposed XRD method, detection limits of less than 1% of mineral and, therefore down to 0.1% lithium oxide, can be reached. Case studies from a hard rock lithium deposit will demonstrate the value of mineralogical monitoring during mining and the different processing steps. Additional, more complex considerations for the analysis of lithium samples from salt lake brines are included and will be discussed.

Towards a regolith mineralogy map of the Australian continent: a feasibility study in the Darling-Curnamona-Delamerian region

Bulk quantitative mineralogy of regolith is a useful indicator of lithological precursor (protolith), degree of weathering, and soil properties affecting various potential landuse decisions. To date, no national-scale maps of regolith mineralogy are available in Australia. Catchment outlet sediments collected over 80% of the continent as part of the National Geochemical Survey of Australia (NGSA) afford a unique opportunity to rapidly and cost-effectively determine regolith mineralogy using the archived sample material. This report releases mineralogical data and metadata obtained as part of a feasibility study in a selected pilot area for such a national regolith mineralogy database and atlas. The area chosen for this study is within the Darling-Curnamona-Delamerian (DCD) region of southeastern Australia. The DCD region was selected as a ‘deep-dive’ data acquisition and analysis by the Exploration for the Future (2020-2024) federal government initiative managed at Geoscience Australia. One hundred NGSA sites from the DCD region were prepared for X-Ray Diffraction (XRD) analysis, which consisted of qualitative mineral identification of the bulk samples (i.e., ‘major’ minerals), qualitative clay mineral identification of the <2 µm grain-size fraction, and quantitative analysis of both ‘major’ and clay minerals of the bulk sample. The identified mineral phases were quartz, plagioclase, K-feldspar, calcite, dolomite, gypsum, halite, hematite, goethite, rutile, zeolite, amphibole, talc, kaolinite, illite (including muscovite and biotite), palygorskite (including interstratified illite-smectite and vermiculite), smectite (including interstratified illite-smectite), vermiculite, and chlorite. Poorly diffracting material (PDM) was also quantified and reported as ‘amorphous’. Mineral identification relied on the EVA® software, whilst quantification was performed using Siroquant®. Resulting mineral abundances are reported with a Chi-squared goodness-of-fit between the actual diffractogram and a modelled diffractogram for each sample, as well as an estimated standard error (esd) measurement of uncertainty for each mineral phase quantified. Sensitivity down to 0.1 wt% (weight percent) was achieved, with any mineral detection below that threshold reported as ‘trace’. Although detailed interpretation of the mineralogical data is outside the remit of the present data release, preliminary observations of mineral abundance patterns suggest a strong link to geology, including proximity to fresh bedrock, weathering during sediment transport, and robust relationships between mineralogy and geochemistry. The mineralogical data generated by this study are presented in Appendix A of this report and are downloadable as a .csv file. Mineral abundance or presence/absence maps are shown in Appendices B and C to document regional mineralogical patterns.