Proceedings of the Workshop on Data Mining for Geophysics and Geology

TL;DR

This paper discusses the application of data mining techniques to large and diverse geoscience datasets, emphasizing their importance in energy, earth sciences, and sustainability, and highlighting recent advances enabled by modern computing.

Contribution

It provides an overview of data mining applications in geophysics and geology, focusing on handling large-scale, heterogeneous data for improved decision-making and efficiency.

Findings

Data volumes in geosciences are rapidly increasing, reaching terabytes per day.

Modern data collection enables real-time analysis, enhancing operational efficiency.

Data mining can significantly improve exploration and production processes.

Abstract

Modern geosciences have to deal with large quantities and a wide variety of data, including 2-D, 3-D and 4-D seismic surveys, well logs generated by sensors, detailed lithological records, satellite images and meteorological records. These data serve important industries, such as the exploration of mineral deposits and the production of energy (Oil and Gas, Geothermal, Wind, Hydroelectric), are important in the study of the earth crust to reduce the impact of earthquakes, in land use planning, and have a fundamental role in sustainability. The volume of raw data being stored by different earth science archives today makes it impossible to rely on manual examination by scientists. The data volumes resultant of different sources, from terrestrial or aerial to satellite surveys, will reach a terabyte per day by the time all the planned satellites are flown. In particular, the oil industry has been using large quantities of data for quite a long time. Although there are published works in this area since the 70s, these days, the ubiquity of computing and sensor devices enables the collection of higher resolution data in real time, giving a new life to a mature industrial field. Understanding and finding value in this data has an impact on the efficiency of the operations in the oil and gas production chain. Efficiency gains are particularly important since the steep fall in oil prices in 2014, and represent an important opportunity for data mining and data science.