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Downhole parameter prediction method based on multi-layer water injection model and historical data-based model

Bingxuan Wu1, Chenquan Hua1, Guobin Ren1

  • 1College of Control Science and Engineering, China University of Petroleum (East China), Qingdao, Shandong, China.

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Summary
This summary is machine-generated.

Predicting downhole pressure and flowrate is crucial for wireless layered water injection systems. This study introduces a multi-layer model that accurately forecasts these parameters, optimizing energy consumption and supporting system deployment.

Keywords:
Downhole parameter predictionModel parameter identificationMulti-layer water injection modelWireless communication

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Area of Science:

  • Petroleum Engineering
  • Wireless Sensor Networks
  • Hydraulic Modeling

Background:

  • Wireless layered water injection tools offer cost-effectiveness and reliability.
  • Underground batteries in wireless systems necessitate energy conservation strategies.
  • Intermittent communication modes lead to data gaps, requiring downhole parameter prediction.

Purpose of the Study:

  • To develop a predictive method for downhole parameters in wireless layered water injection systems.
  • To address energy consumption issues in wireless systems by enabling accurate parameter forecasting.
  • To provide technical support for the widespread adoption of wireless layered water injection technology.

Main Methods:

  • Established a multi-layer injection prediction model based on tubing string hydraulic analysis.
  • Utilized wellhead pressure and flow rate as model inputs.
  • Implemented a time-weighting parameter optimization method for gradual parameter changes.
  • Employed a recursive relationship between layers for layer-specific predictions.

Main Results:

  • The proposed method accurately predicts downhole flowrate and pressure for each layer.
  • Achieved a prediction deviation of less than 5% Full Scale (F.S.).
  • Demonstrated the effectiveness of the time-weighting optimization for model parameters.

Conclusions:

  • The developed multi-layer model effectively predicts downhole parameters in wireless layered water injection systems.
  • The prediction accuracy supports the operational efficiency and energy management of these systems.
  • The method provides a viable solution for data gaps in intermittently communicating downhole tools.