the journey to create a new data...

DAS Image Source: SPE-140561Showing Depth vs Time,

and additional data.

This talk was inspired by Corine Jansonius, Wilfred Berlang, the musings of Floy Baird, and a Lightning Talk by Chuck Smith.

THE JOURNEY TO CREATE A NEW DATA STANDARD,

PRODML - DAS, WITH ENERGISTICS

Presented November 8, 2016 by:

Richard TummersInnovation PM

1

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 2014. • 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.

2Speaker: Richard Tummers, Innovation PM

The role of members in the Energistics Consortium.The project charter.A brief description of the PRODML DAS standard. The full version is at: http://w3.energistics.org/schema/Prodml_v2.0_data_schema_rc.zip

(~15 Minutes)

Introduction

13

Speaker: Richard Tummers, Innovation PM

http://w3.energistics.org/schema/Prodml_v2.0_data_schema_rc.zip

© 2016 Energistics 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.



Global Influence: Industry-Wide

9Operators

8Oilfield Services

15Associations

9Media Partners

14Regulators

45Solution Providers

5Universities


The Distributed Acoustic Sensing Charter

1. Raw Data (~1TB/day/well)

High data sample rates.

As recorded by an IU.

2. Reduced Data

No pain – no gain.

3. Results Data (out of scope)

Used by Decision Makers.

Generates the Value.

time, length along fiber, depth, power,

wavelength, frequency, I, Q, phase,

amplitude, acquisition metadata,

external triggers, related data, …

1. 2.

Sponsored by: Matthias Hartung, Vice President for Technical Data at Shell, Director at Energistics 6Speaker: Richard Tummers, Innovation PM

To exchange a DAS dataset using PRODML, the following is required:

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)

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 N1) Times-Array: Sample Times (1xN1)

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 N2) Times-Array: Sample Times (1xN2)

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 N3) Times-Array: Sample Times (1xN3)

HDF5

XML

Describing DAS data


MeasurementStart Time

Output Data Rate (=Number of Scans /Traces per second)

DAS Interrogation Unit

N

0 1 2 3 4

5678910111213141516171819202122232425262728

…

0 1 2 3 4 5 6 7 8Time

Decimated Output Data (Decimation Factor 4)

Fiber End

Well Head

fiber lengthcorresponding

to a Locus

… … … … … … … … … … … … … … …

……

Time Series for one Locus

Start Locus Index(for measurement)

Number of Loci = 17(8 - 24) recorded

Downhole fiberLoci 5 - N

Spatial Sampling Interval

0 1 2345678910111213141516171819202122232425262728

N

Locu

s Ind

ex0 1 234

Surface fiberLoci 0-4

Casing

PerforatedCasingsection

Productionpacker

Productiontubing

Nomenclature

Locu

s Ind

ex


DAS Data Arrays and Time Arrays

L1

L2

L3

L4

L5

Raw Spectrum (FFT) FrequencyBand Extracted

(FBE)

L1

L2

L3

L4

L5

t1 t2 t3 t4 t5 t6 t7 t8 t9 t10 t11 t12 t13 t14 t15 t16 t17 t18

M1M2

M3M4

M5M6

M7M8

t3 t9t19 t3 t9

𝐹𝑏𝑒1=

1

4

𝑛=5

8

𝑀𝑖

L1

L2

L3

L4

L5

L1

L2

L3

L4

L5

𝐹𝑏𝑒2=

1

4

𝑛=5

8

𝑀𝑖

𝐹𝑏𝑒1

𝐹𝑏𝑒2

M1M2

M3M4

M5M6

M7M8

Example 8-point DFT Example: 2 FBE bands

Example: 5 loci, 21 time samples

WindowSize 8 samples, WindowOverlap 2 samples 𝐃𝐅𝐓 𝒐𝒗𝒆𝒓 𝒘𝒊𝒏𝒅𝒐𝒘

L

N1 N2 N39


Energistics Packaging Conventions (EPC):

XML XML

XML

XML reference

to HDF5 file

XML reference

to HDF5 file

XML reference

to HDF5 file

Data arrays

EPC container is a

ZIP file with XML’s

and related data


One EPC, 2 HDF5 filesH5 files contain data arrays and are called External Parts

XML Describes whole data set

XML Provides reference to External Part Reference (one per HDF5 file)

EPC is a zip file container

For each of the XML files, provides relationships to other files including external HDF5 files

EPC File

Rels folder

DAS Files


DAS PRODML Schema


XML Example DAS Acquisition XML file


HDF5 Contains

Acquisition and dataset

meta data

(copy from XML)

DAS Raw and processed

Spectra

and Fbe data-arrays and

time-arrays

Notes:

• Array times in Unix

time format

• HDF group attributes

contain human

readable time formats

Data Array Time Array

Group attributes

HDF5 tree structure


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…

(~10 Minutes)

BC - Before Charter

215


Fiat Lux – a brief history of light… 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)

…

Rayleigh Scatter – the basis of DAS

Early Optical Technology (1880)16


Oil and Gas Industry Backdrop…

• 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: https://www.eia.gov/dnav/ng/hist/rngwhhdD.htm

$1

$2

$3

$4

$5

$6

$7

$8

$9

$10

Dec

-19

96

Dec

-19

97

Dec

-19

98

Dec

-19

99

Dec

-20

00

Dec

-20

01

Dec

-20

02

Dec

-20

03

Dec

-20

04

Dec

-20

05

Dec

-20

06

Dec

-20

07

Dec

-20

08

Dec

-20

09

Dec

-20

10

Dec

-20

11

Dec

-20

12

Dec

-20

13

Dec

-20

14

Dec

-20

15

Dec

-20

16

Henry Hub Natural Gas Spot Price Dollars per Million Btu

DASPRODMLStandard

Energistics CEO

First DAS

Global Bank Crisis

FirstDTS

First DTS Standard Second DTS Standard

Unconventionals Fiber Breakage

Unconventionals Begins…


https://www.eia.gov/dnav/ng/hist/rngwhhdD.htm

Distributed Temperature Sensing: The 1st Quarter Century…

• First Deployments• Early 1990’s proved feasibility and value from

GigaBytes of data.

• Promote the technology• Industry Primer on DTS released (2003).

• 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).

Rupert Sutherland,

GNS Science and Victoria University of Wellington


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. Speaker: Richard Tummers, Innovation PM 19

Terabytes of “Flow” Data:

Source: Hans den Boer, Peter Panhuis, Andre Franzen, Wilfred Berlang, et al. Speaker: Richard Tummers, Innovation PM

• By 2014, advanced analytics enabled quantitative flow calculations using DAS data transmitted via cell phone.

Stage 4 is “poor”

Stage 3 is “good”

Stage 2 is “best”

“traffic light” of flow over depth and time.

20

https://eu001-sp.shell.com/sites/AAAAB3848/Technology Platform Smart Fields/05 Presentation/movies/SmartProducer_0.3Hz1Hz.avi

The 30 month journey to design and publish DAS standards – May 2014 through November 2016.

(~15 Minutes)

The Project

321


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


Project Plan

Charter(Jun 2014)

Outline(Mar 2015)

Develop(Jul 2016)

Release(Nov 2016)

1. Charter2. Call for Participation3. Plan

1. Use cases2. Data types3. Gap analysis4. Test data sets5. Conceptual model6. Refine project plan

1. Architecture2. Iteratively design and

test standard3. Confirm SEAFOM-

PRODML definitionconsistency

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


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...

4. 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 v2.0.

7. 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.


(~10 Minutes)

The importance of data standards:

425



Think of Standards Like Sheet Music…

•Standards allow companies to play together easily -sharing data, eliminating wasted time, reducing cost and complexity



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.



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.


Although I disagree with the title – I believe this is a thought provoking way to discuss the

role of standards in technology adoption.

REFRIGERATORELECTRICITY

STOVE

RADIOTELEPHONE

CELLPHONE


Questions and Answers


FURTHER DAS RESOURCES


the journey to create a new data...

Documents