Geological data is essential for mining engineering, as it helps to identify, evaluate, and exploit mineral resources. However, analyzing geological data can be a complex and challenging task, requiring various methods, tools, and skills. In this article, you will learn how to analyze geological data in six steps, from collecting and organizing data to interpreting and communicating results.
The first step in analyzing geological data is to collect relevant and reliable data from various sources, such as field observations, maps, boreholes, samples, geophysical surveys, and remote sensing. Depending on the scale and scope of your project, you may need to use different techniques and instruments to gather data. For example, you may use a GPS device to locate and record field data, a drill rig to obtain core samples, or a satellite image to map the surface features.
Creating maps of geological processes, rather than individual elements, is another important aspect of analyzing geological data. This can involve using GIS software to create maps of geological features and processes, such as fault lines, mineral deposits, and groundwater flow. Additionally, machine learning algorithms can be used to identify patterns in geological data and make predictions about future geological events. There are many resources available for learning about geological data analysis, including online courses, textbooks, and YouTube channels like the one mentioned by the user.
Analyzing geological data involves a wide range of techniques and methods. One of the most important aspects of analyzing geological data is to conduct thorough research for existing information. This can involve reviewing literature, geological maps, and other data sources to gain a better understanding of the geological features and processes in the area of interest. Compositional data analysis is another important tool for analyzing geological data. This involves analyzing the relative proportions of different elements or minerals in a sample, rather than the absolute values. Machine learning programs like WEKA, RapidMiner, and Skills.ai can also be used to process geochemical data and identify patterns in the data.
The next step is to organize the data you have collected in a systematic and logical way, so that you can easily access, manage, and manipulate it. You may use different software and databases to store and organize your data, such as Excel, Access, ArcGIS, or GeoSoft. You may also need to convert, format, or standardize your data to make it compatible and consistent. For example, you may need to convert coordinates, units, or projections, or apply quality control measures.
Data collection is a fundamental thing for geological data and with good database management, it would impact the life of mine, reducing cost, and increasing confident level. It is really important.
The third step is to visualize the data you have organized in a graphical or spatial way, so that you can see patterns, trends, and anomalies. You may use different tools and methods to visualize your data, such as charts, graphs, tables, diagrams, cross-sections, or maps. You may also use 3D modeling or animation to create realistic and interactive representations of your data. For example, you may use a 3D modeling software to create a digital terrain model of your area of interest.
In this part, we have so many ways to do a visualization and interpretation, 3D modelling nowadays is already collaborate with machine learning method such as supervised, unsupervised, etc. As a geologist, we can improve the data interpretation with this tools.
The fourth step is to analyze the data you have visualized in a quantitative or qualitative way, so that you can extract meaningful and useful information. You may use different techniques and algorithms to analyze your data, such as statistics, geostatistics, geospatial analysis, or machine learning. You may also use different software and platforms to perform your analysis, such as MATLAB, R, Python, or QGIS. For example, you may use a geostatistical software to estimate the grade and tonnage of your mineral deposit.
The fifth step is to interpret the data you have analyzed in a scientific or engineering way, so that you can understand the geological processes and phenomena behind your data. You may use different models and theories to interpret your data, such as structural geology, petrology, mineralogy, geochemistry, or geophysics. You may also use different sources and references to support your interpretation, such as literature, reports, or experts. For example, you may use a structural geology model to explain the deformation and faulting of your rock formations.
The final step is to communicate the data you have interpreted in a clear and concise way, so that you can share your findings and recommendations with your stakeholders, such as clients, managers, or regulators. You may use different formats and media to communicate your data, such as reports, presentations, posters, or videos. You may also use different styles and languages to communicate your data, depending on your audience and purpose. For example, you may use a technical report to document your data analysis and a PowerPoint presentation to summarize your main results and conclusions.
Presentation is the easiest way and reports are always helpful. Just pour out your abstract data and let's experience make it better each day.