Doing business the 'e-savvy' way pays off for oil company and suppliers
Bibliographic record
Abstract
This report on how Canadian oil and gas company EnCana has worked with Schlumberger on improving the business processes of its US operations is a follow up to the Special Topic feature from DigitalOilfield, published in the January issue of First Break, on the emerging use of e-technology to conduct business more efficiently. Just as every detail of reservoir information is processed to derive the most value, every detail of electronic business transactions can yield immediate and long-term rewards. Within the energy sector, the advantages gained from real-time data for on-the-spot decision-making now extend beyond the realm of improvements in E&P exploration, exploitation and production technology to include business systems and processes. One example of how trading partners can examine ledger processes and implement application-to-application integration comes from EnCana Oil&Gas (USA) and Schlumberger who now claim short- and long-term benefits from doing business electronically. A first milestone in automated electronic exchange of PIDX XML (Petroleum Industry Data Exchange Extensible Markup Language) invoice information was reached in early 2003. Industry players were introduced to true application-to-application integration and a new mechanism that would reduce costs, automate repetitive and manual processes, and shorten cycle times. Since then, energy companies and service firms have been attempting to implement eBusiness processes in the most cost-effective and efficient manner. EnCana first piloted the Digital Oilfield OpenInvoice internet-based eInvoicing at its Rifle, Colorado field in December 2001. OpenInvoice allowed EnCana’s suppliers and employees and authorized users to collaborate on the creation, processing, and approval of invoices and field tickets. For suppliers, the OpenInvoice system was used to automate paper-driven processes by automatically coding line items, tracking invoice inquiries, resolving disputes, and seamlessly linking spend information. Some suppliers already possess automated field data capture and invoicing processes linked to backend Enterprise Resource Planning (ERP) systems. For over 10 years these systems have successfully exchanged large numbers of Electronic Data Interchange (EDI) documents with customers, and today capture and analyze critical business information. At the time EnCana piloted its programme, the OpenInvoice system required suppliers to manually input service delivery information, scan, and upload delivery tickets, code services and log in for dispute resolution as part of the browser-based process. However, it was recognized that the integrated suppliers of EnCana needed an alternative solution to achieve the same benefits. The solution was systems integration.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.010 |
| Scholarly communication | 0.033 | 0.031 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.125 | 0.039 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".