Data mining technology helps you to automatically extract, transform, clean and integrate information from a variety of sources inside the organization and correlate it with public data to increase and enrich the width and depth of the final output. During oil and gas exploration and production lifecycle, we collect, process, interpret, maintain, multiply and manipulate huge data. Normally we store data in various big and small databases (Oracle, SQL Server etc.) as well as on file systems especially in the case of seismic volumes, simulations, models, reports, presentations, and spreadsheets etc. This is the same environment where data mining fits perfectly.
There are various forms of data mining such as text mining, web mining, audio & video data mining, pictorial data mining, relational databases, and social networks data mining. Data mining is thus also known as Knowledge Discovery in Databases since it involves searching for implicit information in large databases. The main kinds of data mining software are:
- Clustering and segmentation software
- Statistical analysis software
- Text analysis, mining and information retrieval software
- Visualization software
Data mining is the automated analysis of large data sets to find patterns and trends that might otherwise go undiscovered. A few popular applications are to:
- Understanding consumer research marketing
- Product analysis, demand and supply analysis
- Telecommunications and so on.
Data mining can also be technically defined as the automated mining of hidden information from large databases for predictive analysis. It requires the use of mathematical algorithms, statistical techniques and analytical skills along with an ability to use software efficiently. Data mining includes several different technical approaches, such as:
- Clustering
- Data Summarization
- Learning Classification Rules
- Finding Dependency Networks
- Analyzing Changes
- Detecting Anomalies
I believe that data mining has arrived on the scene at the right time. This will help petroleum industry to trust and utilize analytics to efficiently make complex decisions, which is not possible without data in right size and coverage.
