New and game-changing developments in geochemical exploration

Mulder, Eduardo F. J. de; Cheng, Qiuming; Agterberg, Frits; Gonçalves, Mário A.

doi:10.18814/epiiugs/2016/v39i1/010

Cited by 9 publications

(2 citation statements)

References 16 publications

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“…Thus, machine learning can summarize and control the entire data volume based on certain artificial restrictions. Therefore, we can reasonably use the idea of machine learning for data processing and prediction [15][16][17]. Numerous studies have employed machine learning to tackle the petrophysical and fracture-related problems.…”

Section: Introductionmentioning

confidence: 99%

Quantitative Prediction of Fractures in Shale Using the Lithology Combination Index

Zhang

Yuan

et al. 2020

Minerals

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Fractures, which are related to tectonic activity and lithology, have a significant impact on the storage and production of oil and gas in shales. To analyze the impact of lithological factors on fracture development in shales, we selected the shale formation from the Da’anzhai member of the lower Jurassic shales in a weak tectonic deformation zone in the Sichuan Basin. We defined a lithology combination index (LCI), that is, an attribute quantity value of some length artificially defined by exploring the lithology combination. LCI contains information on shale content at a certain depth, the number of layers in a fixed length (lithology window), and the shale content in the lithology window. Fracture porosity is the percentage of pore volume to the apparent volume of the rock. In the experiment, fracture porosity was obtained using 50 samples from six wells, by observing rock slices under a microscope. The relationship between LCI and fracture porosity was analyzed based on machine learning, regression analysis, and weighting methods. The results show that LCI is able to represent the impact of multiple lithological factors (i.e., shale content at a certain depth, the number of layers in the lithology window, and the shale content in the lithology window). The LCI within a thickness of 2 m for the lithology window demonstrates a good linear relationship with fracture porosity. We therefore suggest LCI be used for fracture predictions of shale formations from weak tectonic deformation zones. Our proposed LCI and fracture prediction methods also provide implications for sandstone, mudstone, or carbonate formations under similar processes.

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Section: Introductionmentioning

confidence: 99%

Quantitative Prediction of Fractures in Shale Using the Lithology Combination Index

Zhang

Yuan

et al. 2020

Minerals

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“…Separation of geochemical anomalies from background has always been a major concern of exploration geochemistry [5]. The search for methods that can make this analysis quantitative and objective aims not only at the reduction of subjectiveness but also at providing an automatic routine in exploration, assisting the interpretation and production of geochemical maps [6].…”

Section: Introductionmentioning

confidence: 99%

Exploratory Geochemical Studies to Determine the Mineralization Zones Around the Zarshuran Gold Mine

Heidarlaki¹,

Ziaii²,

Afzal³

et al. 2018

IJSEA

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The study area is located in the northern part of Takab, West Azarbaijan Province, northwest of Iran. Since geochemical explorations, especially the drainage sediments, play a very important role in finding promising areas and providing conditions for more detailed exploration. Detection and separation of geochemical anomalies from the field is one of the most important and fundamental issues in geochemical exploration. In this study, using the classical statistcs methods, anomalous values were determined. Other methods used in this study is the concentration-area (C-A) fractal method. This method is a very successful method for separating anomalies from the field due to simultaneous consideration of the frequency and spatial variations of geochemical data. Multivariate statistical analysis including principal component analysis (PCA) was used to obtain anomaly values related to determine the anomaly values. Favorable results for the methods used for this region was presented.

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Predictive Geologic Mapping and Mineral Exploration

Agterberg

2022

Encyclopedia of Mathematical Geosciences

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New and game-changing developments in geochemical exploration

Cited by 9 publications

References 16 publications

Quantitative Prediction of Fractures in Shale Using the Lithology Combination Index

Quantitative Prediction of Fractures in Shale Using the Lithology Combination Index

Exploratory Geochemical Studies to Determine the Mineralization Zones Around the Zarshuran Gold Mine

Predictive Geologic Mapping and Mineral Exploration

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