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Upstream Information Management
A Benchmark study Originally prepared foR total Fina s.a. by the data room. Upstream information management is now available for purchase.
Summary and Prospectus
The Data Room SARL, based near Paris, France was engaged by Total SA to perform a benchmark study of Information Management (IM) in the upstream sector of the world-wide oil and gas sector. The study involved 11 units of international majors in Europe, Canada and the United States which, while operating in different environments, shared many problems in IM. Patrick Fréchu, Director of Research and Data Management with Total SA said "We commissioned the Upstream Information Management Benchmark Study from the Data Room because of their experience in the exploration and production business as well as their expertise in data management." Fréchu went on, "The results of The Data Room's survey have been integrated into our corporate Information Management strategy, providing a sound basis for our decisions in the fields of data management tool selection, investment arbitration and corporate policy".
Digital Trap
Companies deployed IT-intensive solution successfully in areas of established E&P activity, but in frontier areas and New Ventures, more reliance was made of traditional library functions. Of particular note was the position of the participants in the business process cycle. Those having shed traditional library management functions during reorganization reported lost business opportunities as a result. Others, using Asset-focused business units, also reported problems managing data beyond the life-span of an Asset. Some companies reported running into a ‘digital trap’ whereby traditional library functions were disbanded before adequate digital management of data was assured.
Decentralized tools
Neil McNaughton, Director of The Data Room commented, "What interested me most in this study was the fact that some of the simplest ideas had the most impact, whether this was a weekend spent indexing data from dusty cardboard boxes prior to a bidding round or capturing a minimalist subset of information from an asset prior to closure. In a similar vein, one of the partners had enhanced productivity across the board, by initiating a program of home-based training in the use of Office Automation products. In the area of New Ventures, none of the companies deployed ‘big-iron’ IT solutions to the IM problem. Successful companies were those that have either maintained traditional library functions, or those in a ‘post BPR’ phase of development, who were developing relatively light-weight solutions to recording the corporation’s previous experience.” The success of decentralized IT tools such as Intranets and Lotus Notes was also a significant development, as was the extensive deployment of Geographic Information Systems (GIS).
1 Project background and methods 7
2 Abstract 8
2.1 Management and organisation 8
2.2 The application is king......... 8
2.3 Bespoke development is widespread 8
2.4 Standard data models have had limited impact....... 8
2.5 Commercial data management products - early days 9
2.6 Unstructured data management - the digital "trap"........ 9
2.7 Office Automation - inadequate tools?........ 9
3 Main Data Storage and Access Technologies Used.......... 11
4 Analysis 13
4.1 Organisation and sourcing of data management 13
4.2 Master Repositories 13
4.3 Finder 13
4.4 Other Repositories 14
4.5 Project Database(s) 15
4.6 Data Models.... 16
4.7 Data Access technology 16
4.8 IRIS21 visibility from master data browser.. 16
4.9 ArcInfo 17
4.10 Data management by data type 17
4.11 Derived and Interpreted data types 17
4.12 Standards and Formats.. 17
4.13 Media 17
4.14 Rode Encapsulation 18
4.15 Information/knowledge management technologies 18
4.16 Best Practices 18
4.17 Office Automation 19
4.18 Links to Finance and Administration 19
5 Company A Interview 20
Introduction................. 20
Production New Ventures 21
5.1 Exploration New Ventures 23
6 Company A Questionnaire 25
6.1 Data Management Function and Organisation 25
6.2 Sourcing of data management function 25
6.3 Data and information repositories employed 25
6.4 Project database 26
6.5 Standards, and formats.. 26
6.6 Media 27
6.7 Data access technology 27
6.8 Data Management by data type 28
6.9 Best Practices 29
6.10 Derived and interpreted data types 29
6.11 Office Automation 30
6.12 Links to Finance & Administration 30
7 Company B Interview 31
7.1 Introduction..... 31
8 Company B Questionnaire 35
8.1 Data Management Function and Organisation 35
8.2 Sourcing of data management function 35
8.3 Data and information repositories employed 35
8.4 Project database 36
8.5 Standards, and formats.. 36
8.6 Media 37
8.7 Data access technology 37
8.8 Data Management by data type 38
8.9 Best Practices 39
8.10 Derived and interpreted data types 39
8.11 Office Automation 40
8.12 Links to Finance & Administration 40
9 Company D Questionnaire 41
9.1 Data Management Function and Organisation 41
9.2 Sourcing of data management function 41
9.3 Data and information repositories employed 41
9.4 Project database 42
9.5 Standards, and formats.. 42
9.6 Media 43
9.7 Data access technology 43
9.8 Data Management by data type 44
9.9 Best Practices 45
9.10 Derived and interpreted data types 45
9.11 Office Automation 46
9.12 Links to Finance & Administration 46
10 Company E Interview 47
11 Company E Questionnaire 50
11.1 Data Management Function and Organisation 50
11.2 Sourcing of data management function 50
11.3 Data and information repositories employed 50
11.4 Project database 51
11.5 Standards, and formats.. 51
11.6 Media 52
11.7 Data access technology 52
11.8 Data Management by data type 53
11.9 Best Practices 55
11.10 Derived and interpreted data types 55
11.11 Office Automation 56
11.12 Links to Finance & Administration 56
12 Company F Interview 57
13 Company F Questionnaire 61
13.1 Data Management Function and Organisation 61
13.2 Sourcing of data management function 61
13.3 Data and information repositories employed 61
13.4 Project database 62
13.5 Standards, and formats.. 62
13.6 Media 63
13.7 Data access technology 64
13.8 Data Management by data type 65
13.9 Best Practices 67
13.10 Derived and interpreted data types 67
13.11 Office Automation 68
13.12 Links to Finance & Administration 68
14 Company G Interview 69
15 Company G Questionnaire 72
15.1 Data Management Function and Organisation 72
15.2 Sourcing of data management function 72
15.3 Data and information repositories employed 72
15.4 Project database 73
15.5 Standards, and formats.. 73
15.6 Media 74
15.7 Data access technology 74
15.8 Data Management by data type 75
15.9 Best Practices 76
15.10 Derived and interpreted data types 76
15.11 Office Automation 77
15.12 Links to Finance & Administration 77
16 Company H Interview 78
17 Company H Questionnaire 81
17.1 Data Management Function and Organisation 81
17.2 Sourcing of data management function 81
17.3 Data and information repositories employed 81
17.4 Project database 82
17.5 Standards, and formats.. 82
17.6 Media 83
17.7 Data access technology 83
17.8 Data Management by data type 84
17.9 Best Practices 86
17.10 Derived and interpreted data types 86
17.11 Office Automation 87
17.12 Links to Finance & Administration 87
18 Company I Interview 88
19 Company I Questionnaire 92
19.1 Data Management Function and Organisation 92
19.2 Sourcing of data management function 92
19.3 Data and information repositories employed 92
19.4 Project database 93
19.5 Standards, and formats.. 94
19.6 Media 95
19.7 Data access technology 95
19.8 Data Management by data type 97
19.9 Best Practices 98
19.10 Derived and interpreted data types 98
19.11 Office Automation 98
19.12 Links to Finance & Administration 99
20 Company J Interview 100
21 Company J Questionnaire 102
21.1 Data Management Function and Organisation 102
21.2 Sourcing of data management function 102
21.3 Data and information repositories employed 102
21.4 Project database 103
21.5 Standards, and formats 103
21.6 Media 104
21.7 Data access technology 104
21.8 Data Management by data type 105
21.9 Best Practices 106
21.10 Derived and interpreted data types 106
21.11 Office Automation 106
21.12 Links to Finance & Administration 107
22 Company K Interview 108
23 Company K Questionnaire 114
23.1 Data Management Function and Organisation 114
23.2 Sourcing of data management function 114
23.3 Data and information repositories employed 114
23.4 Project database 115
23.5 Project database 115
23.6 Media 116
23.7 Data access technology 116
23.8 Data Management by data type 117
23.9 Best Practices 118
23.10 Derived and interpreted data types 118
23.11 Office Automation 119
23.12 Links to Finance & Administration 119
24 Company L Interview 120
25 Company L Questionnaire 122
25.1 Data Management Function and Organisation 122
25.2 Sourcing of data management function 122
25.3 Data and information repositories employed 122
25.4 Project database 123
25.5 Standards, and formats 123
25.6 Media 124
25.7 Data access technology 124
25.8 Data Management by data type 125
25.9 Best Practices 126
25.10 Derived and interpreted data types 126
25.11 Office Automation 127
25.12 Links to Finance & Administration 127
Project background and methods
This study involves 10 major oil companies based in Europe and North America. From these companies a Total of 11 affiliates participated in the survey. The survey comprised a questionnaire and an interview and was designed to determine emerging standards and practices in the fields of data management, information and knowledge work. This is a vast and many faceted subject and is difficult to study in a rigorous manner. In particular the situation in all of the participating companies is evolving, with many companies moving, or planning to move from legacy systems to commercial data management environments. In view of this, the design of the survey has been open rather than closed. In other words, participants have been encouraged to express their views and to describe both the status quo and plans for the short term. All companies taking part in the study did this with considerable enthusiasm, information management is a great concern to all and a real challenge to get right. While this field is an extremely important one for participating companies and could be considered to be "core business", it is not an area where companies seek to gain competitive advantage and consequently the information divulged in this study very rich and we hope will be of assistance to all involved in this work.
Abstract
2.1 Management and organization
Companies with a strong centralized policy and organization are rare. Naturally centralized companies manage to impose corporate standards, but as soon as a Company has an affiliate of any importance, different practices creep in, and problems with synchronizing databases arise. At the extreme end of this are companies who have undergone a move from highly centralized management to a break up into major autonomous affiliates, themselves with highly independent assets. There is now very little communication between these affiliates on data management practice. One participant (Company E) using the decentralized business model can be said to be entering a "post-modern" era, where there is a serious attempt to re-centralize at least some of the data management function. This has been necessary because of the de-facto loss of the corporate memory due to a focus on short-term results with the abandonment of centralized custody of data. Another centralized Company (F) has adopted a re-centralizing role with the initiation of a world-wide E&P IT program. The latter is perhaps the most ambitious program we have studied especially as it involves a forced cooperation between the two major software vendors.
2.2 The application is king
The application is rightly the focus of E&P computing but this has also created many problems for the data manager. Data transfer and reformatting are major issues. It is often difficult to recognize the conventional "marketing" vision of Application, Project Data Store and Corporate Data Store in the way in which companies operate their data management systems. Some companies use variants on this theme. Others store corporate data in applications. And others again live "from hand to mouth" with data only really managed digitally for "hot" projects. Some companies use the UNIX file system itself as an ad-hoc Project Data Store. Those companies who have taken an all-digital corporate data store option are generally still in the process of populating the data base with legacy data - sometimes after several years of effort. No companies had a centralized repository sufficiently well populated to constitute a first port of call for a new ventures specialist.
2.3 Bespoke development is widespread
Almost all participants have invested considerable time and money in bespoke development. This has usually been in the form of a data model, data browser or both. This development may integrate elements from E&P software vendors, but the most common development "standard" is the widespread use of Geographical Information Systems from ESRI (ArcInfo, ArcView etc.). One of the biggest perceived benefits of in-house developed software is the complete control it brings over data formats and interoperability. Another virtue is the possibility of integrating "world leading" proprietary technologies developed in-house into the interpretation chain. The downside is of course the considerable overhead involved in software maintenance.
2.4 Standard data models have had limited impact
Some companies have implemented data models based on industry "standards" from POSC or PPDM. While these models have helped the database designers, they have had little impact on interoperability. This is partly because application vendors have not generally aligned themselves with these standards. It is also due to the problem of customization. In the relational database world, even small customizations can lead to problems with interoperability and maintenance.
2.5 Commercial data management products - early days
Many companies expressed an intention or were implementing plans to "buy not build" data management solutions. While some have implemented data management solutions from the major vendors, most are in the planning stage. The implementers surveyed are generally themselves in early stages of deployment, with data models only part-populated and data flows under development.
2.6 Unstructured data management - the digital "trap"
Access to unstructured data (text, reports images and other documents) has tended to suffer recently with many librarian functions lost to re-structuring, and with digital technology only providing a partial replacement solution. Companies fall into two camps :
- Good unstructured data managers - those who have maintained legacy library systems in working order
- Sufferers from restructuring and re-organization - many companies report that new business units no longer report information to central libraries and/or these have become dysfunctional following downsizing.
Despite the digital revolution, the effective management of paper data, whether this is in the library or in boxes in off-site storage is still an integral part of good E&P data management. This has given good managers of paper data real competitive advantage especially in the new ventures arena. On the other hand, those companies caught in the "digital trap" - whereby poor digital data management has prematurely replaced good librarian-ship have suffered. Such companies are conscious of the loss of corporate knowledge, of lost opportunities, and of the of the impact that this has on the bottom line.
2.7 Office Automation - inadequate tools?
Office Automation - Spreadsheets, word processors etc. are of course widely deployed. Managing the data and information contained in these documents is usually performed by archiving such documents in their native format, although some companies deploy HTML or Adobe's Portable Document Format (PDF). In most companies, it is still the printed report, archived in the library that makes up the corporate archive.
Companies reported successful use of Lotus Notes groupware allowing for the sharing of information between team members. A serious problem with managing the proliferating Notes databases was reported.
This Benchmark Study of Information Management in E&P was originally prepared under contract by The Data Room for TOTAL S.A. To order the 120 page report, or to request further information, please complete the form below.
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The Data Room,
7 Rue des Verrières,
92310 Sèvres, FRANCE.
(+* (33) 1 4623 9596
: neilmcn@csi.com
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