How big data is impacting measurement operations

Transcription

1 How big data is impacting measurement operations A new approach to leveraging your measurement data Author: Ed Hanks, CEESmaRT Presented by: Ernie Hauser, WEST CONFIDENT IAL

2 Can big data monitoring and analytics have a positive effect on pipeline operating performance? CONFIDENT IAL 2

3 What is CEESmaRT? A cloud-based or enterprise monitoring and analytics service for natural gas custody transfer measurement stations Currently monitors more than 6 meters Provides a large database of historical data, which can be analyzed to answer the question posed The results of that analysis will be discussed in this presentation. CONFIDENT IAL 3

4 Clarifications Automated business logic Enhanced automated business logic Data monitoring dashboards Data analytics Big data: inferential analytics Device connectivity Business intelligence: typically device level Multiple devices and actions instructions CONFIDENT IAL 4

5 Big data defined Business intelligence Uses descriptive statistics with data with high information density. Measures things, detects trends, etc. Big data Uses inductive statistics and concepts from nonlinear system identification to infer regressions, nonlinear relationships, and causal effects from large sets of data with low information density. Reveals relationships and dependencies, and predicts outcomes and behaviors. CONFIDENT IAL 5

6 Value of different stages of big data development The IoT maturity index Stage achieved by Fortune 2 companies with active IoT deployments 1% % Sources: Gartner, 451 Research, Bsquare estimates Device connectivity 2 Data monitoring dashboards 3 Data analytics 4 Development and execution of automated business logic Total available ROI achieved at each IoT maturity stage 1% % Sources: Gartner, 451 Research, Bsquare estimates 5 Enhanced automated business logic Adapted from a BSQUARE slide from the 217 IIOT Conference. CONFIDENT IAL 6

7 Key performance indicators (KPIs) Business KPIs are historical. They summarize what has happened. KPIs are the first step in achieving a broader understanding of the effectiveness and efficiency of actions. Earnings of a business Return on capital investment Efficiency of a process New customers obtained Predicting future events through inductive pattern recognition has the potential to affect outcomes. CONFIDENT IAL 7

8 Pipeline operations Inputs and outputs tracked at custody transfer points. Measured by instrumentation (flow meters, analyzers, pressure and temperature sensors, flow computers) with some degree of uncertainty. The non-zero sum of these measurements, combined with actual gains and losses, is defined as lost and unaccounted for (LAUF) gas. LAUF is a cost. A broad KPI that does not necessarily translate to specific actions for improvement. CONFIDENT IAL 8

9 The process Describe and understand the database. Develop KPIs that quantify performance. Review trends in KPIs to quantify changes in performance. CONFIDENT IAL 9

10 Jan-13 Jul-13 Jan-14 Jul-14 Jan-15 Jul-15 Jan-16 Jul-16 Dec-16 Jul-17 Dec-17 Jul-18 Count of stations and meters The database 25 2 Stations Runs Monitoring growth CONFIDENT IAL 1

11 Jan-13 Jul-13 Jan-14 Jul-14 Jan-15 Jul-15 Jan-16 Jul-16 Dec-16 Jul-17 Dec-17 Jul-18 Count of stations and meters Equivalent years CEESmaRT big data Monitoring growth 25 2 Stations Runs Eq Years CONFIDENT IAL 11

12 Jan-13 Jul-13 Jan-14 Jul-14 Jan-15 Jul-15 Jan-16 Jul-16 Dec-16 Jul-17 Dec-17 Jul-18 Count of stations and meters Bcf/d monitored CEESmaRT big data Monitoring growth 25 2 Stations Runs Bcf/d CONFIDENT IAL 12

13 Jan-13 Jul-13 Jan-14 Jul-14 Jan-15 Jul-15 Jan-16 Jul-16 Dec-16 Jul-17 Dec-17 Jul-18 Count of stations and meters Average meter flow per day [MMScf/d] CEESmaRT big data Stations Runs Avg Flow Monitoring growth CONFIDENT IAL 13

14 Jan-13 Jul-13 Jan-14 Jul-14 Jan-15 Jul-15 Jan-16 Jul-16 Dec-16 Jul-17 Dec-17 Jul-18 Count of stations and meters Equivalent years CEESmaRT big data Monitoring growth 25 2 Stations Runs Eq Years CONFIDENT IAL 14

15 Measure operational performance improvement Number of Events identified per month x Average Resolution time of an event x Impact of the event (average estimated error in Mscf/d) = Lost and unaccounted for gas CONFIDENT IAL 15

16 Events USM transducer or electronics failure Contamination, blockage or liquids in the meter run P or T transmitter out of calibration Communication problems between devices Flow computer calculation problems such as fixed values and configuration errors Chromatograph problems CONFIDENT IAL 16

17 Issues CEESmaRT discovered Issue % of sites Events total Resolution days (avg) Impact ($M) USM Trx & electronics 28% $6.5M Flow computers 18% $2.9M USM operations 23% $1.4M P&T transmitters 23% $.8M Chromatographs 45% $.4M 72% $12M *Results based on data collected from clients over the last three-and-a-half years normalized to 1 stations. CONFIDENT IAL 17

18 Jan-13 Jul-13 Jan-14 Jul-14 Jan-15 Jul-15 Jan-16 Jul-16 Dec-16 Jul-17 Dec-17 Jul-18 Count of stations and meters Events Reliability improvement 25 2 Stations Runs Events Average events per 1 meter stations CONFIDENT IAL 18

19 Jan-13 Jul-13 Jan-14 Jul-14 Jan-15 Jul-15 Jan-16 Jul-16 Dec-16 Jul-17 Dec-17 Jul-18 Count of stations and meters Resolution days Improved response time 25 2 Stations Runs Res Days Average days to resolution CONFIDENT IAL 19

20 Jan-13 Jul-13 Jan-14 Jul-14 Jan-15 Jul-15 Jan-16 Jul-16 Dec-16 Jul-17 Dec-17 Jul-18 Count of stations and meters MMscf Reduction in LAUF exposure Stations Runs ERI ERI (Events x Resolution days x Impact) CONFIDENT IAL 2

21 Jan-13 Jul-13 Jan-14 Jul-14 Jan-15 Jul-15 Jan-16 Jul-16 Dec-16 Jul-17 Dec-17 Jul-18 Count of stations and meters Dollars [$k] Reduction in LAUF cost exposure 25 Stations ERI (Events x Resolution days x Impact) Runs ERI CONFIDENT IAL 21

22 Jan-13 Jul-13 Jan-14 Jul-14 Jan-15 Jul-15 Jan-16 Jul-16 Dec-16 Jul-17 Dec-17 Jul-18 Count of stations and meters Dollars [$k] Total cost savings in LAUF exposure 25 Stations ERI (Events x Resolution days x Impact) Runs ERI Y1 $937,346 Y2 $2,31,941 Y3 $2,981, CONFIDENT IAL 22

23 Conclusion Big data analytics have a positive effect on pipeline operations. The added value is a step change over the dashboard KPIs that have been available and adopted thus far. CONFIDENT IAL 23