THE JOURNEY TO CREATE A NEW DATA STANDARD,

Transcription

1 THE JOURNEY TO CREATE A NEW DATA STANDARD, PRODML - DAS, WITH ENERGISTICS Presented November 8, 2016 by: Richard Tummers Innovation PM This talk was inspired by Corine Jansonius, Wilfred Berlang, the musings of Floy Baird, and a Lightning Talk by Chuck Smith. DAS Image Source: SPE Showing Depth vs Time, and additional data. 1

2 Agenda & Goals 1. Introduction: Understand Energistics member companies and roles. Be familiar with this standards development project charter, and the resulting PRODML DAS standard. 2. BC - Before Charter: Understand the technology innovations that occurred prior to starting standards development in Understand the time to maturity needed to identify the requirements that would justify a new standard. 3. The Project: Be familiar with the project team, schedule, and plan. Understand some of the lessons learned by this project team. 4. The importance of data standards: Be familiar with some correlations between innovation, data standards, and business value. 2

3 Introduction The role of members in the Energistics Consortium. The project charter. A brief description of the PRODML DAS standard. The full version is at: 1 (~15 Minutes) 3

4 What is Energistics? Energistics is a global, non-profit, membership consortium that facilitates the development and adoption of technical open data exchange standards in the upstream oil and gas industry. Membership consists of integrated oil & gas companies, IOCs, NOCs, oilfield service companies, software vendors, system integrators, regulatory agencies and the global standards user community. Standards are developed by workgroups (known as Special Interest Groups, or SIGs) made up of industry experts. In short, the standards are created by the industry for the industry Energistics 4

5 Global Influence: Industry-Wide Operators Oilfield Services Regulators Solution Providers Associations Media Partners Universities 2016 Energistics 5

6 The Distributed Acoustic Sensing Charter Raw Data (~1TB/day/well) High data sample rates. As recorded by an IU. 2. Reduced Data No pain no gain. time, length along fiber, depth, power, wavelength, frequency, I, Q, phase, amplitude, acquisition metadata, external triggers, related data, 3. Results Data (out of scope) Used by Decision Makers. Generates the Value. Sponsored by: Matthias Hartung, Vice President for Technical Data at Shell, Director at Energistics 6

7 Describing DAS data To exchange a DAS dataset using PRODML, the following is required: XML Optical Path: fiber installation components and connections DAS Instrument Box: model, vendor, firmware, etc DAS Acquisition: Acquisition meta-data: job, spatial sampling along the fiber, output rate of the system data Calibration/Mapping: mapping of spatial samples along fiber to physical location (x,y,z) HDF5 Datasets: types, sampling along fiber, time-sampling Raw: spatial samples (loci, channels) along the fiber for all sampled times (time-samples) Data Array: Loci x Sample Times (L x N 1 ) Times-Array: Sample Times (1xN 1 ) Spectrum/FFT: spatial samples along fiber for all time-windows with transform (FFT) was calculated Data Array: Loci x FFT-size x TimeWindows (L x M x N 2 ) Times-Array: Sample Times (1xN 2 ) FBE: spatial samples along fiber for all frequency bands for all time-windows for which extracted Data Array: Loci x FrequencyBands x TimeWindows (L x B x N 3 ) Times-Array: Sample Times (1xN 3 ) 7

8 Measurement Start Time Output Data Rate (=Number of Scans /Traces Decimated per second) Output Data (Decimation Factor 4) Nomenclature DAS Interrogation Unit Spatial Sampling Interval Casing Production tubing Locus Index Surface fiber Loci 0-4 Well Head fiber length corresponding to a Locus Start Locus Index (for measurement) Number of Loci = 17 (8-24) recorded Downhole fiber Loci 5 - N Time Time Series for one Locus Locus Index Production packer Perforated Casing section Fiber End N N 8

9 DAS Data Arrays and Time Arrays Raw Spectrum (FFT) Frequency Band Extracted (FBE) Example: 5 loci, 21 time samples WindowSize 8 samples, WindowOverlap 2 samples Example 8-point DFT DFT over window M7 M8 M7 M8 M4 M5M6 M4 M5M6 M1 M2M3 M1 M2M3 Fbe1= n=5 Example: 2 FBE bands M i Fbe2= n=5 M i Fbe1 Fbe2 L1 L1 L1 L1 L L2 L3 L2 L3 L2 L3 L2 L3 L4 L4 L4 L4 L5 L5 L5 L5 t1 t2 t3 t4 t5 t6 t7 t8 t9 t10 t11 t12 t13 t14 t15 t16 t17 t18 t19 t3 t9 t3 t9 N 1 N 2 N 3 9

10 Energistics Packaging Conventions (EPC): XML XML XML EPC container is a ZIP file with XML s and related data XML reference to HDF5 file XML reference to HDF5 file XML reference to HDF5 file Data arrays 10

11 DAS Files One EPC, 2 HDF5 files H5 files contain data arrays and are called External Parts EPC is a zip file container EPC File XML Describes whole data set XML Provides reference to External Part Reference (one per HDF5 file) Rels folder For each of the XML files, provides relationships to other files including external HDF5 files 11

12 DAS PRODML Schema 12

13 XML Example DAS Acquisition XML file 13

14 HDF5 Contains Acquisition and dataset meta data (copy from XML) DAS Raw and processed Spectra and Fbe data-arrays and time-arrays HDF5 tree structure Data Array Time Array Notes: Array times in Unix time format HDF group attributes contain human readable time formats Group attributes 14

15 BC - Before Charter Innovations and situations prior to 2014 that affected the maturation and identification of the potential values of DAS technology. Standards can rapidly follow useful applications 2 (~10 Minutes) 15

16 Fiat Lux a brief history of light Rayleigh Scatter the basis of DAS Early Optical Technology (1880) 1870: Fiber Optic - total internal reflection 1871: Rayleigh scattering 1880: Bell Photophone 1920 s: Brillouin and Raman scattering 1950 s: First practical glass fiber 1965: Data via fiber 1967: Fotonic sensing Kissinger patent 1977: GTE telephone backbone 1981: Single mode (long-haul) fiber 1988: Trans-Atlantic fiber (TAT-8) 1990 s: First Oil and Gas DTS deployments 1995: OTDR (GR-196 Issue 1) 16

17 Oil and Gas Industry Backdrop Henry Hub Natural Gas Spot Price Dollars per Million Btu First DTS $10 $9 $8 $7 $6 $5 $4 First DTS Standard Second DTS Standard First DAS Unconventionals Fiber Breakage DAS PRODML Standard $3 $2 $1 Unconventionals Begins Global Bank Crisis Energistics CEO The earlier DTS Fiber Optic Technology has evolved for a quarter century. Since DAS began in 2009, the industry has had extensive organizational reductions and adjustments in both IT and the business. Data Source: 17

18 Distributed Temperature Sensing: The 1 st Quarter Century First Deployments Early 1990 s proved feasibility and value from GigaBytes of data. Promote the technology Industry Primer on DTS released (2003). Rupert Sutherland, GNS Science and Victoria University of Wellington Develop industry exchange standard POSC defines WITSML standard (2005). Innovate, Deploy, and Improve: Major applications for Injection and Flow. PRODML evolves (2014 v1.3, 2016 v2.0). Commercial Cloud databases (2015). 18

19 TeraBytes of DAS Hydraulic Fracturing Data: 1. Started with a high value, relatively simple use case. 2. Designed proprietary tools and workflows to harvest value. 3. De-risked major business and IT aspects of the technology. 4. Co-visualized and analyzed hundreds of TeraBytes of raw data. 5. Learned and published lessons. Source: Mathieu Molenaar, Kiran Somanchi, et al. 19

20 Terabytes of Flow Data: By 2014, advanced analytics enabled quantitative flow calculations using DAS data transmitted via cell phone. Stage 4 is poor traffic light of flow over depth and time. Stage 3 is good Stage 2 is best Source: Hans den Boer, Peter Panhuis, Andre Franzen, Wilfred Berlang, et al. 20

21 The Project The 30 month journey to design and publish DAS standards May 2014 through November (~15 Minutes) 21

22 DAS Standards Project Team Roles Leaders: 1. Shell 2. OptaSense Contributors: 3. Baker Hughes 4. BP 5. Fotech 6. Schlumberger 7. Silixa 8. Weatherford 9. Ziebel Reviewers: 10. Chevron 11. Tendeka Observers: 12. AP Sensing 13. Dynamic Graphic 14. ExxonMobil 15. OPC 16. OSISoft 17. Total 22

23 Project Plan Charter (Jun 2014) Outline (Mar 2015) Develop (Jul 2016) Release (Nov 2016) 1. Charter 2. Call for Participation 3. Plan 1. Use cases 2. Data types 3. Gap analysis 4. Test data sets 5. Conceptual model 6. Refine project plan 1. Architecture 2. Iteratively design and test standard 3. Confirm SEAFOM- PRODML definition consistency 4. Review optical path changes with DTS Standards Team 5. Usage Guide and other documentation 6. Consensus on readiness to release 1. Put on website for public review 2. Communicate to public to encourage review 3. Review and respond to public comments 4. Post release marketing plan 5. Post release support plan 23

24 Lessons Learned 1. Level the workload of your volunteer resources. The DAS SIG was formed more easily because the DTS SIG was disbanding at that time. 2. Leverage global strengths in your team. 3. Leverage existing standards (DTS, SEGY, HDF, XML, LAS, CSV, etc.). Don t re-invent binary or ASCII DTS standards were so robust and useful, that they were able to evolve from POSC WITSML to Energistics PRODML. 5. Don t assume old standards are fully mature. 6. Champions are required for major revisions, such as PRODML v Manage multiple time frames (sometimes hours, sometimes years). 8. Economics affects standards development, since maturity is built by business applications. 9. Engage with the business opportunity early And stay engaged through the cycle of innovation. 10. Adoption of standards can be driven by contracts. 24

25 The importance of data standards: 4 (~10 Minutes) 25

26 Think of Standards Like Sheet Music Standards allow companies to play together easily - sharing data, eliminating wasted time, reducing cost and complexity 2016 Energistics 26

27 The Value of Energistics Standards Standards deliver cost savings for companies and the whole industry. Data can be exchanged seamlessly between users, partners, service companies, operators & regulators. Better data quality leads to better business productivity. Standards eliminate time lost resolving data quality issues related to incompatible formats and manual entry. Standards allow legacy data to be re-used and re-analyzed using more recent tools and models. Standards ensure that trusted and accurate information is available for a rapid response to any safety incident Energistics 27

28 A Compelling Business Case Standards save time, increase efficiency, reduce lost time, reduce complexity and potentially help save lives. Energistics standards reduce costs for individual companies and for the industry as a whole. The ROI is clear and compelling Energistics 28

29 Although I disagree with the title I believe this is a thought provoking way to discuss the role of standards in technology adoption. STOVE ELECTRICITY REFRIGERATOR TELEPHONE RADIO CELLPHONE

30 Questions and Answers 30

31 FURTHER DAS RESOURCES 31