Well operations team deals with series of Well log data through real time system and any other data exchange system. This data is streaming through different channels and with a naming convention implemented by the respective originator of the data or the system. The goal of the data is to be used for Studies and Operations. This paper mentions the implemented data workflow to deal with Well log data sources, channels, mnemonics and sharing through a standardized workflow.
The Real time data streaming through WITSML servers is connected directly into Subsurface application by proper authorization and access. The data naming conventions was collected from all the specific service provider, and it was than mapped with standard naming that is used in the organization. The data consists of several different type of mnemonics. Example could be XXX_P10H, XXX_ROBB, XXX_MCIA, XXX_GRM2, where XXX stands for vendor specific name. The frequency of Real time data depends on the streaming and some time it takes time to update data. In parallel, memory data for the same wells are made available to the Operations team through a defined exchange system. A mapping was developed between Log mnemonics from the vendors and the standard naming convention proposed by the Operations team. Python scripts were used to automatically rename and map any log mnemonics and aliases coming to the subsurface application. For the memory data, other scripts work, which goes to the individual LAS files and check the mnemonics and changes them back to standard naming convention.
Implementation of the mapping and python scripting has helped engineers achieve their objectives in efficient way. They do not have to worry about individually renaming the specific log and channel names. Data quality has improved by comparing the real time and memory data sources. User experience has enriched and enhanced with the implemented data mapping and standardization workflow. For example, in case of Neutron log sometimes, users must change units from % to Fraction for using it for other Petrophysical calculations. This process is now automated, and data gets converted with the defined standard.
By mapping and standardizing the way of comparing data sources, logs and channels has improvised the data quality, data sharing and data governance related issues. This is a continuous process which requires further improvements and result oriented approach.