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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

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

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Networked Drillstring LWD/MWD/RSS Tools 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 Todays Wellbore Data

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Networked Drillstring LWD/MWD/RSS Tools Interface SubNetworked Drillstring Distributed Sensors 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 Along-String Distributed Measurements

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Networked Drillstring LWD/MWD/RSS Tools Interface SubNetworked Drillstring Distributed Sensors Real-time wellbore sensor arrays

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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

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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.

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Divide and Conquer? "Nearly independent" parameters No Flow P(h) = g h cos + P top – 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

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Divide and Conquer? "Nearly independent" parameters Flow P(h) = g h cos + P fric + P top – 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 P fric

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

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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

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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

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Model strategy 1.Parameter search in old model for best match with BHP 2.Estimate pressure at sensor 1 along string 3.If match with sensor, save model parameters 4.Work backwards from sensor 1 to estimate BHP. 5.Repeat for sensor 2,3,.. 6.Combine BHP-estimates Model OK? MeasurementModel estimate

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

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Conclusions 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.

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Recommendations 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

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Slide 19 of 5 Thank you

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