Navigating the intricacies of digitizing data and related processes, particularly within the realm of oil wells and subsurface reference datasets, posed ongoing challenges for a prominent oil and gas company’s upstream production department. The classification of wells, wellbores, and subsurface data typically involves categorizing them based on parameters such as well type (e.g., vertical, directional, horizontal), completion method (e.g., open hole, cased hole), and production characteristics (e.g., primary, secondary, tertiary recovery). This classification helps understand the characteristics and behavior of different types of wells and optimizes management strategies accordingly. Historically, this classification has been a largely manual process. Recognizing the imperative of modernization, the Upstream business unit acknowledged the inadequacies of their current manual processes, impeding scalability, efficiency, and productivity. With users reliant on email for change requests, followed by labor-intensive validation studies and manual adjustments across multiple environments, the process spanned four disparate tracking sheets, resulting in sluggish response times, inefficient data processing, and suboptimal resource utilization.
This organization now has a single trusted repository of well codes for all users to access. The data model supports the current use case and is flexible enough to accommodate the adoption evolution into the PPDM model and expansion into OSDU standards.
Users can request new and updated reference data. This process is fully automated, allowing for timely review and response. The efficiency of data handling allows the Upstream to shift their efforts to higher-value initiatives.
With the initiative to modernize their subsurface database repository with as much automation as possible, a multi-phase data management program was introduced. Phase 1 involved migrating a subset of tables from an on-premise subsurface database into an MDM platform (TIBCO EBX) running within an Azure cloud infrastructure. The subset tables included well codes, wellbore codes, completion data, and surface facility types (the infrastructure and equipment that are installed above ground to support the extraction, processing, and transportation of oil and gas produced from the well). Each entity of data was referred to by multi-names/terms, and thus, the consolidation of duplicate code terms and associated relationships to the other data entities required a master data management process.
Based on industry knowledge and incumbent experience with the organization and high MDM skillsets, D3Clarity was selected as the vendor of choice to design and implement a well code reference data solution.
D3Clarity implemented a data model solution that was flexible enough to capture all relevant reference data for well codes and classification, assign aliases, and manage technical metadata of where each attribute originated from. Data validation was added to ensure data integrity.
Workflow processes were designed to manage the addition of new codes, modification of codes, and retirement of codes. Automating real-time notifications to allow for timely responses to new information was crucial to this solution. A journaling method of history was designed, as historical records needed to be retained within the new solution.
I’ve been working with D3Clarity since 2017. They've helped us migrate over our very first application from Azure to AWS and have been with us since. They have a very knowledgeable & professional staff that have helped us in our digital migration from our on-prem data centers to the AWS cloud.
D3Clarity provided us with invaluable insights, visualizations, topography maps and tools to help us make better decisions with our cloud infrastructure.
We selected D3Clarity to architect and migrate our Customer Services application to AWS and I can confidently say that their services are “top notch.”
D3Clarity went above and beyond. They are great to work with and create long lasting relationships!
Great partnership with D3Clarity!
D3Clarity’s experience with multiple MDM vendors, helped make the implementation a success.
D3Clarity was asked to help a very large client in the oil and gas industry with a digital data transformation
Assisted in the establishment of the Enterprise Data Governance Framework
Choosing the Right Master Data Management Platform