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Industry Solutions > Upstream Oil & Gas > Well Drilling Data

Exploration Well Drilling Data

Complete well life cycle data management is a critical activity for every effective oil and gas producer. The challenge in managing diverse types of well data (such as geospacial data, land and geological prognosis, drilling information, licensing, field operational information, testing and completion data) is compounded if there are no standards and data quality processes in place.

Whether there is a local regulatory compliance requirement or a need to be more effective servicing operational and non-operational wells, data quality plays a vital role. Adding to this equation, corporate mergers and acquisitions produces a challenging set of problems:

Data is stored in different formats and technologies
Data originating on legacy systems that violates constraints on new systems with stricter data rules
Orphaned data because legacy systems often do not enforce referential integrity
Historical data is missing

Well Data Profiling Solutions

Understanding the potential for improving data quality is an important first step before embarking on a data transformation project. The following is a subset of the type of well data that we can check for consistency and completeness:

Consistent Use of Well Header Information (such as well name, API/UWI, status, field, operator, etc.)	Valid Geospatial Mapping Data and Survey Data	Drilling Parameters Consistency
Missing Important Well Data Attributes	Valid Completion Information	Consistent Use of Unit of Measures
Standardized Company & Vendor Name Spellings	Implemented Consistent Date Formats	Test Data Standards
Standardized Geological Information.	Incorrect Attributes in Incorrect Fields	Possible Record Duplication Across Systems.
Matched Well Data with Cost Records	Operator Information Validated	Existence of Unprintable Characters

Well Data Transformation and Conversion Solutions

Whether the client project is one to consolidate a collection of legacy systems onto a new enterprise Drilling and Completions system, or to validate and cleanse the data across systems, DataVera provides the capability to standardize and clean data, to find and match duplication information, and for merging the data into the target dataset.

DataVera is a revolutionary data quality service that, unlike traditional data quality methods, uses a continually growing library of reusable and automated data solutions that transforms the data in less time with a higher quality.

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