Abstract
Using historical data to aid the planning of future operations is a very promising area of data analytics. Many organisations have their own data reporting tools alongside a number of benchmarking tools for use in performance analysis. One commonly used tool for both purposes are locally installable spreadsheet packages. In using this type of tool, the ability to analyse data and communicate with other applications is very limited. This limitation results in less accurate performance analysis, which leads to inaccuracy and less detailed analysis.
Using a number of different methods/tools for the same purpose is a problem that is heavily embedded in today’s Oil & Gas culture. This not only doubles or trebles costs, but leads to a sparsely populated and vague data model that cannot be used effectively for data analysis.
By standardising the way data is recorded, the process can be altered so that input data is recorded in one single entity and any analysis can be performed from one place. Using this model, the process can be expanded from Internal-Regional benchmarking to Internal-Global benchmarking, meaning that global data can be logged in one place and the same model used for all analysis.
Structure becomes very apparent in Daily Drilling Reporting. Many companies use very different applications, formats and codes to report data. This lack of standarisation causes a number of problems.
‘How can data that is logged with different degrees of accuracy be compared?’
For example, if one solution logs all BHA time under a single entity ‘BHA’ and another logs individual segments for ‘Making up BHA’, ‘Run in hole BHA’ and ‘Pull out of hole BHA’, how can time be sliced in the first solution so that each category can be analysed accurately?
Through actively streamlining all input data to a managed, centralised database, data analysis and performance engineering can be improved, so that future well planning can be improved. This can clearly result in cost reduction and performance improvement.
