Well Code Reference Data Master Solution

CASE STUDY

4-MINUTE READ

[alt_text prompt_guidance="Describe a successful business outcome from a D3Clarity professional services client implementation project based on post title"]

Our Client

[alt_text meta_key="client_name" prompt_guidance="this D3Clarity professional services client received high-value business outcomes by hiring D3Clarity for this project"]

This Oil and Gas company is one of the world’s largest publicly held international oil and gas companies. It refines crude oil, produces, transports, trades, and sells petroleum products, and manufactures lube base stocks and finished lubricants.

The Challenge at Hand

Navigating the intricacies of digitizing data and related processes, particularly within 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.

Innovative Solutions Unleashed

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. Data handling efficiency allows the Upstream to shift their efforts to higher-value initiatives.

Transformative Results Achieved

A multi-phase data management program was introduced with the initiative to modernize their subsurface database repository with as much automation as possible. 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 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. Thus, consolidating duplicate code terms and associated relationships to the other data entities required a master data management process.

Based on industry knowledge, incumbent experience with the organization, and high MDM skill sets, D3Clarity was selected as the vendor of choice for designing and implementing a well-coded 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 about where each attribute originated. 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.