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SPE 150370 Getting the Most out of Networked Drillstring

SPE 150370 Getting the Most out of Networked Drillstring. Petersen, Sui, Frøyen, Nybø Center for Integrated Operations in the Petroleum Industry & SINTEF Jackson, Veeningen, NOV IntelliServ. Downhole data through Networked Drillstrings Opportunity for modeling A proof of concept

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SPE 150370 Getting the Most out of Networked Drillstring

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  1. SPE 150370Getting the Most out of Networked Drillstring Petersen, Sui, Frøyen, NybøCenter for Integrated Operations in the Petroleum Industry & SINTEF Jackson, Veeningen, NOV IntelliServ

  2. Downhole data through Networked Drillstrings Opportunity for modeling A proof of concept Conclusions and recommendations Agenda

  3. Networked Drillstring Today’s Wellbore Data • Data measured at surface and in the BHA (MWD) • Conditions along-string inferred or modeled • BHA data limited by mud-pulse telemetry rates • Almost impossible to accurately monitor entire wellbore in real-time LWD/MWD/RSS Tools

  4. Networked Drillstring Along-String Distributed Measurements • Increased bandwidth – via Networked tubulars (wired drill pipe) - bidirectional 56,000 bps • Along string measurements technology • Enhanced BHA measurements (density and quality • Accurate & effective real-time decision making Distributed Sensors Networked Drillstring Interface Sub LWD/MWD/RSS Tools

  5. Using distributed sensor data • Need a model to interpret the data and to see the implications • Expect distributed sensor data to: • Provide redundancy • Improve accuracy • Reveal new phenomena • Most models are designed around measurements at the top and bottom only

  6. Networked Drillstring + Advanced Dynamic Drilling Simulator • Drilling simulator: • High resolution parameters (fine spatial grid) • Small timesteps • Dynamic 2-D temperature model • Measurements • Direct: Pressure and Temperature • By combining model and measurements: • Mud densities, cuttings density, cuttings loading, reservoir fluid type and densities, slip relation, fluid viscosities, wall roughness, heat capacity and conduction, background temperatures, etc.

  7. Divide and Conquer? "Nearly independent" parameters No Flow • P(h) = r g h cosq + Ptop • Integrated density – between measurements • Densities (P,T) information obtained at previous measurements • Local temperature measurements • Other temperature information given at previous measurements • From temperature curves – Temperature vs. time • Obtain detailed formation background temperature

  8. Divide and Conquer? "Nearly independent" parameters Flow • P(h) = r g h cosq + Pfric + Ptop • Integrated density – fairly well known from previous measurements • Flow velocity fairly well known from diameters and pump rate • Viscosity and wall roughness can be obtained from Pfric

  9. High rate data acquisition – Model matching: Reliable parameter space DeviationsModel data & Measurements mismatch CausesCuttings loading Open hole washout Kick Wellbore breathing/Loss of circulation Measurement error Etc. Each deviation has a separate "fingerprint" and can be discerned using appropriate software.

  10. Experiment • A real-time drilling simulator has been developed by SINTEF • The simulator was altered to output data as it would appear from a fictional drilling operation rich in distributed sensors • The "simulated sensor readings" were input to a simplified wellbore model predicting BHP. • The simple model was altered to make use of distributed data

  11. Simulated operation: • Pumping 200 l/min for 5 minutes, then stop. • Lowering the bit and tag bottom • Start drilling, pumping 1000 l/min for 60 minutes, drilling at 20 m/hr. • Circulate clean for 60 minutes

  12. Model strategy New model parameter calibrated! OK? OK? More accurate and reliable BHP prediction Measurement Model estimate

  13. By combining redundant measurements in space and time, we can calibrate the model and get: A detailed view of the situation along the whole well Predictive power for the whole well Safety by redundancy The flow around the BHA is a complicating factor Difficult to calculate BHP from pressure above BHA and vice versa Parameters remain uncertain to some degree, since the sensors don't slide past the BHA components. Conclusions

  14. Design simulators and that make use of parallel processing (model tuning & high bandwidth) Simulate sensor configurations w.r.t: redundancy, accuracy and ability to detect drilling problems Consider multiple sensors along the BHA More robust and accurate BHP-measurements Hole-cleaning problems visible in high resolution Especially relevant for MPD and long open-hole sections Recommendations

  15. Thank you Slide 19 of 5

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