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Oil fields of the future: real-time oil and gas operations

Integrated Operations Update David Archer, POSC Integrated Operations SIG Meeting Stavanger, Norway 18 November 2005. Oil fields of the future: real-time oil and gas operations. Onshore Facilities. Offshore Facilities. Decision Centers. new capabilities – much more data; much more exposure.

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Oil fields of the future: real-time oil and gas operations

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  1. Integrated Operations UpdateDavid Archer, POSCIntegrated Operations SIG MeetingStavanger, Norway18 November 2005

  2. Oil fields of the future: real-time oil and gas operations Onshore Facilities Offshore Facilities Decision Centers new capabilities – much more data; much more exposure

  3. Trondheim External experts Bergen Service Company’s onshore operation centre External experts Stavanger Real time data Control room offshore Aberdeen Real time data Operator’s onshore operation centre * Data integration * Information * Visualisation * Knowledge * Decisions * Actions Remote collaboration room Integrated operations

  4. ∆ Smart Systems The basic approach of all “smart technology” is measure-model-control • measure system properties • model actual vs desired behaviour • derive required correction parameters (adaptive control) • implement control Acquire Control Model IntOPS Analyze IntOPS = Integrated Operations Source: Shell

  5. Acquire Control IntOPS Model Analyze Time Scales (106 range) Business Headquarters Slower cycle Capacity Planning Design - Asset life cycle and installed based maintenance or growth - Supply Chain Management & Market and customer demands [months/years] - Planning of injection/production plan and resources Planning drilling and workover resources Operational Planning - [months/years] Supply Chain Management & Market and customer demands - Time-scale Automation level Opening and closing wells or partial completions - Scheduling of injection/production plan and resources Scheduling - Adjusting well operating parameters [days/months] - SCADA systems for coordinating flow stations and pipelines - Supervisory Control - Gas distribution/optimization on a pipeline network [minutes/hours] - Monitoring wellheads, multiples and flow stations Regulatory Control - Flow, pressure and temperature in wells and separator [sec/minutes] - Fuel injection to produce heat out of a boiler Fast cycle Well & Surface facilities Source: Saputelli SPE 83978

  6. The Problem? • Theorem 1: 50% of the problems in the world result from people using the same words with different meanings • Theorem 2: The other 50% of the problems results from people using different words with the same meaning Stan Kaplan, Risk Analysis, Vol. 17, No. 4, 1997

  7. Board Economics Reservoir Production Engineering Geology Expl Petrophysics Petroleum Geology Engineering Drilling Production Facilities Engineering Engineering Engineering Drilling Completion & Production Geophysics Operations Workover Operations POSC Standards / SIGs Epicentre™ Data Model Reference Data Standards E&P Catalogue Standards Practical Well Log Standards Industry Dictionary Data Store Solutions SIG Business Objects eRegulatory SIG NDR Meetings IntOPS SIG XML exchange standards, design guidelines, profiles WellHeader, WellPath, WellLog, LogGraphics, Production Reporting, DTS, …

  8. E&P Subject Areas: WITSML Coverage Board Economics Reservoir Production Engineering Geology Expl Petrophysics Petroleum Geology Engineering Drilling Production Facilities Engineering Engineering Engineering Drilling Completion & Production Geophysics Operations Workover Operations Can we use this image to portray the growth in WITSML coverage?

  9. E&P Subject Areas: WITSML Coverage General Board • WellPath • Well Wellbore • Trajectory • CRS, Projections • Units of Measure Economics Reservoir Production Engineering Geology Expl Petrophysics Petroleum Geology Engineering Drilling Production Facilities Engineering Engineering Engineering Drilling Completion & Production Geophysics Operations Workover Operations Enhancements for raw, calculated and planned Well Path data,coordinate systems, and units.

  10. E&P Subject Areas: WITSML Coverage Board General Economics Reservoir Log,WellLog Production Engineering Geology Expl Petrophysics Petroleum Geology Engineering Drilling Production Facilities Engineering Engineering Engineering Drilling Completion & Production Geophysics Operations Workover Operations Enhancements for wireline as well as LWD log data.

  11. E&P Subject Areas: WITSML Coverage Board General Economics Reservoir Production Engineering Geology Expl Petrophysics Petroleum Geology Engineering Network Model Volume Report Activity Report Drilling Production Facilities Engineering Engineering Engineering Drilling Completion & Production Geophysics Operations Workover Operations Enhancements for Production beginning with Volume and Activity Reporting, continuing with PRODML towards Optimization.

  12. E&P Subject Areas: WITSML Coverage Board General Economics Reservoir Production Engineering Geology Expl Petrophysics Petroleum Geology Engineering Drilling Production Facilities Engineering Engineering Engineering Drilling Completion & Production Geophysics Operations Workover Operations We have a pending request to establish a Geophysical SIG.Such a SIG could lead to WITSML Geophysical data exchange Standards.

  13. E&P Subject Areas: WITSML Coverage Board General Economics Reservoir Production Engineering Geology Expl Petrophysics Petroleum Geology Engineering Drilling Production Facilities Engineering Engineering Engineering Drilling Completion & Production Geophysics Operations Workover Operations At a future time, we could consider the viability of data exchange Standards for facility data, reservoir data, economics data, etc. filling out the E&P space.

  14. E&P Subject Areas: WITSML Coverage Board General Economics Reservoir Production Engineering Geology Expl Petrophysics Petroleum Geology Engineering Drilling Production Facilities Engineering Engineering Engineering Drilling Completion & Production Geophysics Operations Workover Operations This would call for close cooperation with other industry groupsto avoid duplication of effort and ensure smooth transitions.

  15. PRODML: A Shared Solution for Upstream Oil and Gas Companies to Optimize Their Production • What? • Project focused on optimization of oil and gas production • Who? • BP, Chevron, ExxonMobil, Shell, Statoil, eProduction Solutions, Halliburton, Invensys, OSIsoft, Petroleum Experts, Schlumberger, Sense Intellifield, TietoEnator and POSC • What? • Production optimization involves integrating real time data from specialty, multi-vendor software applications and streamlining work processes to enable oil and gas field operational efficiencies • Build on success of WITSML™ - develop the necessary XML-based data exchange solutions as an open industry standard • Extend the WITSML™ ‘architecture’ to include data needed for field production optimization • How? When? • Drive towards commercial software products to improve data exchange and work process efficiency in production optimization - over a 12 month timeframe • POSC will maintain the standard and make it publicly available

  16. Joint Work of Richard Carter, Todd Dupont and Henry RachfordControl of Gas Flow in Pipelines Why is it Hard, What Can We Do about it, and Why do We Care?

  17. Consider a Typical Pipe • 60 Miles Long • 47 inches Inside Diameter • 1000 Microinches Roughness • Pressure, p(t), at Inlet • Flow, q(t), at Outlet, where t is time Inlet Outlet 60 miles, 47” inside diameter. q(t)=Qout p(t) = Pin

  18. Consider a Simple Scenario

  19. Settling q Toward a New State • Steady State @ t=0 • Pin = 850 psia • Qout = 1842 MMSCFD • Temp = 60 oF • Set Qout = 2090 MMSCFD @t=0 • Hold boundaries constant for t>0

  20. Relaxation Time, tr . Let andδ(x,t) = p(x,t) - p(x,T), for 0 < x < L, to< t < T. From any pipeline state fix p at inlet, q at outlet, to cause a state change. Then for T >> to, we find tr = 46.5 minutes, to = 10 minutes

  21. Introduce Sensors [ S(P), S(Q) ] S(Pin),S(Qin) S(Pout),S(Qout) q(t)=Qout p(t) = Pin Outlet Inlet

  22. What Does This Mean for a Real Pipeline System? • Response to control takes hours • Controls to Achieve One Goal may Interact Unexpectedly with Others Look at an Example

  23. 300-Mile 5-Station Pipeline SP2(t) SP3(t) SP4(t) SP5(t) SP1(t) Out In 55 mi 60 mi 50 mi 45 mi 40 mi 50 mi q(t) p(t) Out04 q4(t)

  24. A Simple Scenario • Begin @ Steady State with OUT-End Flow 1500, Station 4 Delivery 450 (in MMSCFD) SPk(0)=800 psia, k=1,…,5 (in Control) • Hold p(t) @ ‘IN’ at 825 psia (0:00 to 24:00). At 09:00 increase Delivery at OUT to 1950 MMSCFD for 5-Hours, return to 1500 • Delivery at 24:00 is Same as at 00:00, so Make End State Same as Start State • Use Simple Control: All Setpoints stay 800 • Call this Scenario 1.

  25. 300-Mile 5-Station Pipeline SP2(t) SP3(t) SP4(t) SP5(t) SP1(t) Out In 55 mi 60 mi 50 mi 45 mi 40 mi 50 mi q(t) p(t) Out04 q4(t) Pin(t)=825 SPk(t)=800 Qout4(t)=450 Qout(0-9)=1500; Qout(9-14)=1950; Qout(14-24)=1500

  26. Observations on Delivery • 5-Hour Increase at OUT adds 450 MMSCFD. This Adds Same as Out04 Flow • 450 Increase Cannot be Supported at Steady State (Max Steady Increase is 150) • Total Initial Gas in Pipe: 1.07 BCF (Initial State Linepack) • Extra Delivery is 93.7 MMSCF, or 8.7% of Linepack

  27. Initial Pipeline State

  28. Scenario 1: All Stations SP=800

  29. Scenario 1: Station 1, 1 Day

  30. Scenario 1: Station 2 Control Interchange

  31. Scenario 1: Station 5, 1 Day

  32. Scenario 1 Deliver OUT-End? Ouch!

  33. Scenario 1: Final StateDay’s End: 2.4% Loss in Linepack

  34. Scenario 1: % Linepack Change

  35. Scenario 1 Fails. What Should Be the Control? For this, Enumerate Goals: • Make Deliveries above Minimum p • Do not Violate Maximum Allowable p • Do not Deplete the Pipeline, e.g., Achieve the End-of-Day Target State • Always Maintain Control, i.e., Never Default Control to Station Maximum • Minimize Fuel Usage, Emissions

  36. How Can We Find Controls? • Recall p(t), q(t), q4(t) are Specified by Users • We Need to find SPk(t), k=1, 2, …, 5 • Guess the five SPk(t) functions. Recall 900 PSIA is maximum value for any SPk(t) • Simulate Results, Compare with Goals • Use Trial and Error to Satisfy Goals With Experience, guessing and trial and error will improve

  37. Alternatively, Guide the Trial and Error with Mathematics • Define the Control Set S = SPk(tn), k =1,…,5, n = 1,…,23, say, i.e., tn = n, i.e. 115 numbers • Begin as Before: Take SPk(tn) = 800 • Interpolate in time between Control Values and use Interpolated Values to Simulate the Gas Day • Quantify Missed Goals as a Functional, J • Calculate Gradient of J with Respect to S • Iterate to revise SPk(tn), so as to Minimize J. • Call Resulting Control Scenario 2

  38. INITIAL STATE THE SAME

  39. Scenario 2: External Flows

  40. Scenario 2: Station 1 Performance

  41. Scenario 2: Station 2 Performance

  42. Scenario 2: Station 3 Performance

  43. Scenario 2: Station 4 Performance

  44. Scenario 2: Station 5 Performance

  45. OUT-End Delivery?

  46. Scenario 2: End-of-Day State • Pack only 0.16% less than original

  47. Scenario 2: Flows, % Pack Change

  48. Compare Scenario Results 1 2

  49. Conclusions • Mathematical Optimization Finds a Control to Achieve Goals in 1-2 Minutes Clock Time • If Delivery were Infeasible, this Fact Would have been Found just as Fast • If Loads Change During Day, Simply find New Controls for the New Schedule again in 1-2 Minutes Clock Time

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