Exploration and development decisions rely on interpretations that are based on log data. Locating and assessing the full scope of data available across proprietary, vendor and edited inventories are daunting and typically manual tasks. Assembling a dataset for interpretation is often one of the most time-consuming aspects of valuing assets and identifying targets.
Firms often rely on basic file naming conventions to determine the contents of raster and digital log data. This results in extensive manual inspection of the contents and loading data into applications for review, which creates little value and negatively impacts application performance.
With its dynamic data model, EDM’s Log Management solution allows firms to unlock the value of their log data assets and accelerate discovery via an intuitive user interface. By exposing the breadth of that data, users can quickly query aspects such as curve types, data coverage, source, audit history and data currency, selecting data as required and exporting data that is application-ready.
Business rules are implemented to solve data quality issues by identifying and automatically correcting prevalent errors, such as incorrect units of measure, missing units, unknown mnemonics and improper value ranges. Log processing can also be used to reclassify mnemonics, add audit tags or even normalize curve values, making the data user-ready.
EDM can be implemented on-premise, in-cloud or as a managed service leveraging industry-leading cloud technology and application management capabilities. The latter option enables firms to reduce implementation times, future-proof and outsource many human resource-intensive tasks.
EDM provides a single end-user view for query and analysis beyond log data. This includes well header, production, cores, directional surveys, seismic, formations and rigs.
By appending important additional information (such as vintages, the time of the last update, file location, associated documentation, historical transformations and normalizations), EDM gives users comprehensive information about the data. This improves search and query capabilities.
Enterprise data dictionary and glossary
Users can leverage a centralized metadata repository to accelerate the mapping, classification, validation and integration of log data.
Alerting and straight-through-processing
Event-driven alerts inform users when a new log file is available or changes in status, as well as when updates have occurred. Straight-through-processing (STP) automates log processing, including consumption, normalization, quality control, exception management and delivery to consuming applications.