Application of Real-Time Fluids Data to Reduce Uncertainty in Casing-to-Casing Time
- Dale Jamison (Halliburton) | Robert Williams (Halliburton) | Aidan Porter (Halliburton)
- Document ID
- Society of Petroleum Engineers
- SPE/IADC International Drilling Conference and Exhibition, 5-7 March, The Hague, The Netherlands
- Publication Date
- Document Type
- Conference Paper
- 2019. SPE/IADC Drilling Conference and Exhibition
- 7 Management and Information, 6.3 Safety, 7.2 Risk Management and Decision-Making, 1.6 Drilling Operations, 7.2.1 Risk, Uncertainty and Risk Assessment
- Real-time, Reduced Well Construction Time, Optimization, ROP, Fluids
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Uncertainties in the drilling process result in safety factors or safety margins sufficient to minimize risks in the drilling process. These safety margins represent inefficiencies in the system. This paper will discuss a method for reducing uncertainty as it relates to well bore pressures and hole cleaning to eliminate or reduce these inefficiencies, quantify the rates of penetration that can be achieved, and illustrate the expected wellbore pressures generated by these rates of penetration.
When data is collected manually, the nuances of fluid changes are lost between property measurements. This paper will illustrate the difference between calculating equivalent circulating densities (ECD) with manually collected mud report data and fluid properties collected in real time and the impact that this can have on optimizing the rate at which the operator can drill and trip pipe.
A patent-based methodology will be presented, in which real-time drilling and fluids data are captured and utilized to model ECD pressure data related to the bore hole. The actual and modeled data are statistically analysed to infer information about how rapid a rate of penetration (ROP) may safely be employed to optimize drilling results.
Data will be presented demonstrating the impact that small improvements in fluid parameters and drilling operations can have over the course of drilling a well.
The role that a real-time hydraulics software model plays in providing predictive analytics for ROP optimization will also be discussed. Predictive analytics enable operators to look several stands ahead of the bit to determine if the ROP drilled will cause issues in the future. This enables the identification of the maximum ROP that can be drilled versus optimizing instantaneous ROP. This enables operators to optimize casing-to-casing time.
|File Size||1 MB||Number of Pages||11|