Introduction to April Focus: Data & Data Management

Welcome to the printed GeoConvention edition of the RECORDER. The focus is “Data and Data Management”. It is amazing how many articles were gathered by Special Coordinator Trudy Curtis and Technical Editor Kristy Manchul. Trudy and Kristy began gathering material for this back in October. As with all our editions, it takes time to gather papers and to work with the authors to put together an edition. There are also many others behind the scenes who have helped with editing of these articles that are not mentioned here.

Parts of this edition will be reprinted in the PPDM Foundation's magazine and will be shared across the two organizations. It is important for the RECORDER to work with other organizations to be able to give our members and readers a better selection of papers.

It seems currently to be appropriate to talk about data and data management because of all the talk about Data Science. Many E&P companies are looking at Data Science in terms of automation to improve efficiency and productivity and reduce costs in the activities that are performed in the exploration and development of oil and gas, such as determination of where to drill, the completions, and finally, the production process. Data Science is a multi-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data (Wikipedia, 2019).

The key with Data Science is the use of structured and unstructured data, and this is what this edition of the RECORDER is about. In order to work with the data, it needs to be prepared properly, such as by applying standards, cleansing, and normalization of the data. Data management is not just the preparation, analysis and storage of the data, but it is also involved with the governance of the data and in enforcing how the data should be used.

The seven articles in this edition offer a broad perspective on data and data management.

Overview of Distributed Fiber-Optic Sensing and the Value of its Data in Asset Optimization

This article reviews what is Distributed Fiber-Optic Sensing, (DFOS), how the data is acquired, and how can it be used. DFOS data is unlike well logs and seismic normally used by geoscientists because it is dynamic. Many are viewing DFOS as data that can be used as a feedback to what is happening in the field and how the reservoir responds.

New Canadian Well Identifier System

Most in the industry use the Unique Well Identifier (UWI). It is generally used as the primary key in our applications and databases to track and report on our assets regarding planning wells, accounting, engineering, budgets, etc. It was designed primarily for vertical wells that at one time dominated the industry, but now most in the industry are drilling horizontal wells and soon, multi-horizontal wells off one borehole to reduce costs and lower the breakeven price of development. With these changes in drilling, much has changed, and our way of identifying, tracking and managing our wells needs to be modernized. The UWI will continue as an intelligent descriptor, but the new primary identifier will be the Canadian Well Identifier System (CWIS). CWIS has been collaboratively designed by leading industry experts, for industry, and the work was facilitated by a standards organization (the Professional Petroleum Data Management (PPDM) Association).

Google Your Way to Maximum Geoscientific Value

With all the data that geoscientists have access to, it seems they are constrained by the limited toolkits available. This paper looks at methodologies and open-source software tools that can provide more efficient access to structured and unstructured data.

E&P Companies, Different Types of Data, Fairway Mapping and Geomodels

E&P companies are using data to drive big economical decisions, including the sanctioning of a new play, and are moving away from geoscientists and engineers working as individuals on the data, creating their own maps and analysis towards working together collaboratively, using a geomodel as the repository of the data across the area. To be able to create a geomodel, standards need to be used so that the data is consistent across the area. As companies are moving towards Data Science, they are now starting to adhere to standards.

Geophysical Data Compliancy – Utilizing Technology

For many geophysicists it is not just the data that they are concerned about, but from a legal perspective they need to understand what data they are entitled to use for an implicitly defined purpose and timeframe. This is defined within the “Master License Agreement” (MLA) between the company which is the licensee of the data and the Speculative Seismic Company, the licensor. Each MLA is different and can take months to negotiate.

The oil and gas industry is an ever changing and complex environment due to merger and acquisition (M&A) activities, regulatory obligations, contractual laws, and obligations to other exploration companies. This article explores how corporations can use technology and process to manage this complex dataset and achieve governance.

The Future of Data and Data Management

Data Managers generally spend half of their time receiving, validating and preparing data that has come to them in digital form. By doing this, they are trying to reduce data attenuation, which is the decay of data every time it's moved from stakeholder to stakeholder, or from process to process. Data attenuation has deep roots in the social, cultural and technological history of the oil and gas industry.

The Cloud: ASK before you ACT

Data Management vendors like CGG are transforming data management from a support function to a value generator. Companies are expecting these data management service providers to deliver solutions to enable their E&P digitalization strategies, as they move towards adopting emerging digital technologies, such as digitization of the oil field, machine learning and public cloud services.

These new technologies can be exciting and game-changing. It is important to define the desired outcome before jumping fully into any new technologies, ensuring that all factors are considered prior to choosing a solution.

Upcoming Events in Data Science and Data Management

For those who would like to learn more about Python programming for machine learning on their own, there is a group called Calgeopy which meets regularly to have a beer and talk about programming. They plan to have a Geoscience Hackathon May 10 & 11 which may be fun to attend. To register, please go to seisware.com/hackathon.

There will also be a Data Management and Intelligence Conference in Calgary at the University of Calgary, May 22-25, 2019, which will look at: data science, business analytics, streaming data analytics, data management, data modeling, data architecture, blockchain and cryptography, data governance, data stewardship, machine learning, and artificial intelligence, to name some of the topics. If you wish to learn more about data management and data science, this is for you. To learn more about this event please go to dmc-conf.com.

Acknowledgements to this Edition

We wish to thank Bonnie and Lawrence Luft, who have been the RECORDER’s printers since 2003, for all their work – not just on this edition, but on the past editions of the RECORDER. The name of their company is Printman, a commercial printing and lithographic company based in Calgary.

Starting with the June edition, the RECORDER committee will be handling the formatting of all the articles to be posted online, as a cost saving measure.

Thank you, Bonnie and Lawrence, for over 16 years of service to the RECORDER.

We would also like to thank Ruth Peach for all her work to sell advertise space for this printed edition.