The NDR in 2012: New Challenges and New Solutions. Dale Blue Global Practice Manager Landmark Services NDR11 Kuala Lumpur 23 October 2012

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1 The NDR in 2012: New Challenges and New Solutions Dale Blue Global Practice Manager Landmark Services NDR11 Kuala Lumpur 23 October HALLIBURTON. ALL RIGHTS RESERVED.

2 Disclaimer direction, is intended for informational purposes only and, unless otherwise agreed in writing, shall not be incorporated into any contract. Landmark makes no representation about the accuracy, reliability, completeness or timeliness of the information provided herein and the information may be revised at any time without notice. The development, release and timing of any features or functionality This no warranty, express or implied and Landmark assumes no liability in connection with the use of information contained herein Nothing in this presentation should be construed as granting any license or right to use the property of Landmark without the express written consent of Landmark and information presented herein may be subject to applicable existing non-disclosure agreements. The trademarks, service marks and logos displayed herein are the property of Landmark. All text, images, graphics and other materials in this presentation are subject to the copyright and other intellectual property rights of Landmark 2012 HALLIBURTON. ALL RIGHTS RESERVED. 2

3 Recurring Themes from Day 1 New Datatypes Grav/mag Interpreted Data Shale Field Development (fracture data, microseismic) Field and Pre-stack Seismic Data User Accessibility to Data 2012 HALLIBURTON. ALL RIGHTS RESERVED. 3

4 Recurring Themes from Day 1 New Datatypes Grav/mag Interpreted Data Shale Field Development (fracture data, microseismic) Field and Pre-stack Seismic Data User Accessibility to Data 2012 HALLIBURTON. ALL RIGHTS RESERVED. 4

5 New Data types - Grav/Mag ASCII or binary formats Geospatial locations Requires entitlements of subsets 2012 HALLIBURTON. ALL RIGHTS RESERVED.

6 New Data types CSEM Controlled Source Electromagnetic Typically binary formats (H5EM-TS) Source + Receivers (like seismic) Requires entitlements of subsets 2012 HALLIBURTON. ALL RIGHTS RESERVED.

7 New Data types Interpreted Data: Well Tops Complimentary to logs Can be used for QC purposes Stratigraphy Provides wellbore formation information Requires wellbore level entitlements Needs to be compatible with user applications 2012 HALLIBURTON. ALL RIGHTS RESERVED.

8 PetroBank Roadmap and beyond Velocity data Phase 1 Velocity data in SEGY High volume ASCII files on Disk / TSM only (not in DB table) Grav Mag phase 1 Grav and Mag Load and index measured and processed data files Spatial line view Entitlement Search, select, request, unload CSEM Phase 1 Station Receiver data Well data Phase 1 Well tops MDS Web Phase 2 COPEX load Tools Work on PetroExplorer Velocity Phase 2 Grav Mag phase 2 Property Grid Survey/data polygon Fixed navigation ref points CSEM Phase 2 Towline source data MDS Web Phase 3 Load Prestack Load Cultural Seismic Trades v2 Tentative: Local Prestack unload pilot Platform migration RCP Align with PE/PH on New Portal based on DS Web? Replace NetTape on Linux Replace DMU QC, preprocessing utilities with commercial tools MDS Web Phase 3 Well data phase 2 Stratigraphy SEGD HALLIBURTON. ALL RIGHTS RESERVED.

9 Recurring Themes from Day 1 New Datatypes Grav/mag Interpreted Data Shale Field Development (fracture data, microseismic) Field and Pre-stack Seismic Data User Accessibility to Data 2012 HALLIBURTON. ALL RIGHTS RESERVED. 9

10 Shale Field Development 2012 HALLIBURTON. ALL RIGHTS RESERVED. 10

11 Integrated Asset Model for Field Optimization 2012 HALLIBURTON. ALL RIGHTS RESERVED. 11

12 Recurring Themes from Day 1 New Datatypes Grav/mag Interpreted Data Shale Field Development (fracture data, microseismic) Field and Pre-stack Seismic Data User Accessibility to Data 2012 HALLIBURTON. ALL RIGHTS RESERVED. 12

13 NDR Processing Company Cycle Time: Weeks - Months Oil Company 2012 HALLIBURTON. ALL RIGHTS RESERVED. 13

14 Data Store or NDR Processing System Cycle Time: Hours - Days Interpretation System SEG-Y SEG-Y SEG-D ASCII NAV PetroBank MDS SeisSpace- ProMAX Direct data I/O to interpretation projects DecisionSpace Geosciences 2012 HALLIBURTON. ALL RIGHTS RESERVED. 14

15 Recurring Themes from Day 1 New Datatypes Grav/mag Interpreted Data Shale Field Development (fracture data, microseismic) Field and Pre-stack Seismic Data User Accessibility to Data 2012 HALLIBURTON. ALL RIGHTS RESERVED. 15

16 Web-based Map and Data Search 2012 HALLIBURTON. ALL RIGHTS RESERVED. 16

17 Index Search with Industry Categories 2012 HALLIBURTON. ALL RIGHTS RESERVED. 17

18 Recurring Themes from Day 1 New Datatypes Grav/mag Interpreted Data Shale Field Development (fracture data, microseismic) Field and Pre-stack Seismic Data User Accessibility to Data 2012 HALLIBURTON. ALL RIGHTS RESERVED. 18

19 Building Blocks for Data Governance Roadmap for Success Establish a Foundation Build Quality Best Practices E&P Master Data Manage Retention and Security Data Discovery Gather Metadata Define Business Terms Understand current best practices globally Enterprise Data Quality Services Maturity Model Traceability and Impact Analysis Roadmap E&P Data Management for Multiple Domains Create and Manage Hierarchies Data Stewardship Manage Retention and Subset Policies Information Retention Security and access needs Governance Policies Processes 2012 HALLIBURTON. ALL RIGHTS RESERVED.

20 Data Principles Stewardship Standards Availability Processes and Quality Management Data Stewardship Model does not exist. Data Owners, if any, evolve on their own during project rollouts (i.e. self appointed data owners). Data standards unknown and/or inconsistent across the business(s). No data repositories are available. Complete lack of procedures or controls for key data operations of create, read, update & delete. No knowledge capture or archiving processes in place. Data Stewardship Model d oes not exist. Owners comm issione d in the sh ort-term for specific projects & initiatives. Stewardship tends to be in form of Data Teams or Super User s that manage all data. Key data defined in the short-term for specific projects & initiatives. Standards are not leveraged from project to project and change often. Disparate set of data repositories exist as a result of specific projects & initiatives. Little or no synch/communication across these tools. Short term procedures or controls for key data operations of create, read, update & delete. Limited archiving driven only by space constraints. D C Defined Data Stewardship Model exists. Stewardship Model is loosely applied to key data entities. Key data standards exist to those who know where to look. Multiple sets of definitions exist because no rationalization/standardiz ation occurs. Multiple data repositories that synchronize and/or communicate via bespoke interfaces. Limited procedures or controls for key data operations of create, read, update & delete. Data archiving defined only for key data entities. Data Governance A B Data Stewardship Model is implemented for the key data entities. Governance process regularly reviews this model and its application, updating and improving as needed. Single set of data standards exist for the key data entities. Definitions are published to a central location that is accessible to other programs, projects and users in secure manner. A single integrated data repository acts as the system of reference (single version of the truth). Other systems access data from the central integrated repository. Defined & consistent set of quality processes for key data operations of create, read, update & delete. Key data is proactively monitored so that knowledge capture occurs at optimal times. Data Stewardship Model has been extended such that the majority of data entities are now governed in a consistent manner. Data standards extended beyond just key data entities. Common data definitions used throughout the businesses & functions. Central data repository is optimized via standard data collection & distribution mechanisms. Data accessible to other programs, projects and users in secure manner. Defined & consistent set of quality processes extend beyond just key data. End-toend automated acquisition to archive processes optimize the life-cycle management of all data. SmartVision for Information Management Clients Business Goals & Objectives Clients Information Process and Data Flows Clients E&P Systems Business Strategy and Operating Confirmation Evaluate Data Stewardship and Governance Process Capture Business Requirements Capture Business Processes and alignment with initiatives Assess Information, Application & Technology Architecture Assessment Compilation and Evaluation Strategy and Roadmap Development Data Maturity Model Level 1 - Initial Level 2 - Reactive Level 3 - Defined Level 4 Managed Level 5 - Optimized Data Governance Model Profile and discover enterprise data and establish a baseline Proactively address quality and perform root cause analysis Discover Define Measure & Apply Monitor Define business terms, reference data and governance policies Apply and maintain rules for key business processes PEOPLE PROCESSES TECHNOLOGY Strategy/Assessment Report Knowledge & Best Practices Identified Business Value Initiatives & Roadmap 2012 HALLIBURTON. ALL RIGHTS RESERVED. 20

21 Conclusions New Datatypes Easy to add the technology Standard formats need to be defined Business rules need to be understood up front Shale Field Development Proper field optimization requires much more than fracture data and microseismic Field and Pre-stack Seismic Data Relatively easy to store and index Need to define the business and use cases User Accessibility to Data Consumerization of IT makes back-office data management obsolete 2012 HALLIBURTON. ALL RIGHTS RESERVED. 21

22 Questions 2012 HALLIBURTON. ALL RIGHTS RESERVED. 22

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