Tough times meant that attendance was down at the 17th SMi E&P Data Management conference, held earlier this year in London. Some may wonder what else can be said on the topic of upstream data. Quite a lot it would seem as the SMi event’s coverage expands to new domains (construction data), geographies (Brazil, Kuwait) and subject matter.
Sergey Fokin of Total’s Russian unit described a pilot investigation into business continuity—measured as mean time to disaster. The investigation targeted geoscience along with cross functional activities such as data management, geomatics and IT with an assessment of data criticality. What happens if a particular office or function is unavailable due to a power cut or a major IT issue? How long can the business continue to function? What data and processes are affected? What contingency plans are in place? One measure of disruption is mean time to disaster—the length of time the business can carry on unaffected. But some events may be harder to categorize. For instance, if a geology cabin burns down during drilling, it may be hard to make a decision on where and when to perforate. The potential financial loss from a perforation in the wrong place may be far higher than the cost of a few days of downtime. So a simple mean time to disaster analysis may fail to capture the risk. Fokin observed ‘You can’t just guess—you need to base such decisions on the facts.’
The study has led to major reorganization with a duplicate backup site in a remote facility and disaster recovery kit available in the server room along with training and testing. The disaster recovery architecture includes auto sync with Vision Solutions’ ‘Double-Take’ and NetApp SnapMirror. Critical apps such as Gravitas, Geolog, Petrel, Total’s Sismage and remote Eclipse are available in under two hours. Multiple stakeholders were involved, IT, G&G, HSE and support services. Critical GSR (check paper) processes are now available in under four hours at the backup site and several notebook computers are available for critical GSR activities.
Mikitaka Hayashi (from Japan-based EPC JGC Corp) showed how Aveva Smart Plant has revolutionized construction data management and handover. Hayashi recapped the difficulty of plant and equipment data management during construction and (especially) handover to the owner operator. Despite many attempts to build on industry standards such as ISO 15926, the solution here is a commercial one, Aveva SmartPlant. This supports complex activities such as concurrent engineering and data management with multiple rapid changes early on in a project’s lifetime. It can be hard to keep the many stakeholders happy. JGC Corp employs a data steward for process control systems deployment and instrumentation. It has developed its own JGC ‘engineering data integrity and exchange’ tool (J-Edix) for populating its data warehouse and sees joint EPC and O&M data management as the way ahead.
Kuwait Oil Co. (KOC) offered two presentations on its production data and IT architecture. Khawar Qureshey showed how a comprehensive line up of software and in-house developed tools are connected with Schlumberger’s Avocet workflow manager. The aim is to have standard optimization models and processes across data acquisition, analysis and into the E&P database. This involves using multiple tools and interfaces and in house IT/integration expertise is ‘developing gradually.’
Schlumberger’s venerable Finder database, the main data repository, has been customized for KOC. Schlumberger’s Avocet has likewise been extended with a field back allocation module. Other solutions have been developed for various artificial lift scenarios. A field data quality and optimization system (Fdqos) has been developed in-house using mathematical programming techniques to optimize over the whole workflow. Fdqos delivers recommendations/strategies (open well x, close well y, raise/decrease production from well z) combining facilities data from Finder with production rate estimates from Decide! The solution has now been deployed across a dozen gathering centers. KOC is now working to integrate Fdqos with its P2ES ERP system and with the Halliburton-based Kwidf digital oilfield.
Grahame Blakey (GDF Suez) observed that often schematics show GIS as at the center of the upstream technology world. This is wrong! Exploring for and producing oil and gas is our core business and needs to be at the center of the picture, with a constellation of disciplines and software around it. GIS then plugs in to any one of these tools as a valuable enabler. The key then to GIS is integration. This can be at the technology level—but also at the corporate strategy level. GDF Suez’ approach to GIS and other IT integration leverages the Prince II framework. GIS is integrating a plethora of applications and domains but always inside the overarching E&P data architecture. There is a ‘deliberate effort not to build a GIS silo.’ Blakey recommends avoiding the GIS word and prefers to speak of ‘mapping for the masses.’ But under the hood, a lot is going on. Data QC with automated update jobs, training, integration with SharePoint, the Flare EP Catalog and more. GDF now requires GIS-formatted data from its contractors. In the Q&A Blakey opined that 3D functionality in GIS was ‘underwhelming.’
Dan Hodgson spoke from the heart and from 20 years of experience of technology refresh projects, latterly with UK-based DataCo. Hodgson classifies technology refresh projects as minor (once per year—an app upgrade), intermediate (app refresh every 3-5 years) and enterprise, every 10-15 years with a change in the whole subsurface portfolio. The latter may take a year to do and cost hundreds of millions. These used to be Landmark upgrades, more recently they have been to Petrel/Studio. Technology has moved from Unix to Linux and from Linux to Windows. There is no handbook available for an enterprise upgrade or technology refresh. If there was a book you would have to jump straight away to page 492, ‘troubleshooting!’ At the Schlumberger forum last year, Chevron presented a $300 million technology refresh that resulted in a ‘25% productivity increase.’ But Hodgson warned that for the last Studio project he was involved in, ‘nobody knew the product, including Schlumberger.’ In another, data migration required a tenfold increase in disk space. Data migration can take an unexpectedly long time. You may have 10 terabytes to shift but the database only ingests takes 200GB/day. Hodgson recommends avoiding a single vendor refresh. Multiple vendor plus in-house resources is best. A lot can go wrong. Asked in the Q&A if he recommended a project management framework, Hodgson replied that while the majors all use framework-type approaches, what is really key is a good project manager. Asked why a company might embark on a $300 million project he expressed a personal opinion that such moves are not driven by a business case, more by emotional decisions and peer pressure. ‘Maybe it was just time for a change.’
Petrobras’ Laura Mastella showed how closely data management and a business case are related. Petrobras’ geologist’s focus recently shifted from clastics to carbonates and needed more data on the company’s cores and cuttings. Petrography was a key enabler and required easy access to all data types for interpretation. Enter Petrobras’ ‘Integrated technology E&P database’ that replaced Excel-based data hoarding. The system was five years in the making and now provides a single entry point to multiple systems, linked by a unique well identity/table and controlled vocabularies for petrography and other domains. Mastella advises ‘make friends with the lab rats, otherwise they’ll stay with their spreadsheets.’ Users get an integrated view of rock data via a dashboard of lithotypes and summary poro perm data. The system ‘brings rock data into the decision making process.’
Wolfgang Storz presented a subsurface data quality management (DQM) project at RWE–DEA. There are notionally as many as ten dimensions of data quality but Storz prefers a simple split between formal and technical DQM. The formal side comprises the quality rules while the technology performs the conformance checking. Nonetheless there is overlap and always a ‘credibility’ issue, which requires subject matter experts for judgement. In the end the notion of a ‘single version of the truth’ that is valid for every data type may be an illusion—especially for more subjective information like formation tops. RWE has cherry picked the PPDM business rules. After checking commercial offerings RWE decided to roll its own solution. Storz found the IT guys were really good at coding business rules. DQM metrics are now visible as traffic light displays and also in map view with a standard DQ symbology. Storz concluded that DQM needs to be a part of the business culture. Data managers need to have high status and competency to push back to geoscientists.
Hussain Zaid Al-Ajmi presented KOC’s partially automated E&P data validation (PADV). PADV seeks to harmonize access to different data sources and to reduce data gaps and redundancy. Halliburton’s Power Explorer is deployed as a front end to a master Open Works repository with authenticated data and standard naming conventions. Schlumberger’s Finder, eSearch, LogDB and GeoFrame now sit behind Power Explorer. KOC has worked to automate data workflows and business rules with scripts. The PADV is now considered a KOC best practice.
Chris Frost (DataCo) offered insights into document migration into an EDMS. Frost is also a hands-on coder and likes to challenge internal processes, support internal tool development and provide support for scripts. Frequently document managers lack the scripting skills needed to perform data mining and folder re-organization that is required prior to migration and will use a time consuming and error prone manual approach. On the other and, hand coding from scratch has its own costs and risks. Enter DataCo’s ‘IQ’ toolkit which, according to Frost, provides a happy mean between hand coding and labor intensive approach. IQ offers stored procedures in SQL Server for deduplication, taxonomy building and key words search. Documents or equipment tags can be recognized (even on scans), classified and captured to a SQL Server database. More from SMi Conferences.
© Oil IT Journal - all rights reserved.