HOLE CLEANING OPTIMISATION MODEL Osvaldo Tchissola-1009243Gordon BotterillMSc Drilling and Well EngineeringBACKGROUNDHole cleaning represent a major challenge in directional and deviatedwells, when improperly managed it can lead to severe hole problemssuch as mechanical pipe sticking , poor cementing, steeringproblems, formation fractures, excessive torque and drag.Throughout years, a lot of research has been done to the determinethe causes of poor hole cleaning and significant improvement hadbeen achieved. However real time optimisation still needs furtherimprovements to reduce the amount of time spent on wiper trips, orreducing cost by early detection of poor hole cleaning that could leadto NPT.This project attempts to create a real time hole cleaning optimisationmodel that analysis the predicted downhole conditions, and thendetermines the required parameters to efficiently clean the hole.Later on during drilling operations the models tracks well data in realtime to check the amount of cuttings removed from the hole. Thusallowing in the early stage detecting the lagging amount of cuttings.Aim:The aim of this project is to develop an integrated hole cleaningmodel that can be used to optimise hole cleaning during drillingoperations. It will anticipate the cuttings concentration in the welland estimate the minimum parameters to reduce cuttings in theannulus. Then, during drilling, the model receives real-time data tocheck if the well is being cleaned properly.Objectives:• Gain a high level of understanding of cuttings transport in deviated wells.• Analyse how several factors impact cuttings transport.• Understand how poor hole cleaning can be detected during drilling operations.• Estimate drilling parameters for optimum hole cleaning.• Develop awareness of good drilling practices for good hole cleaning.
CONCLUSION AND FURTHER WORKConclusionThe model was built based on several equations developedthrough laboratory experiments. Based on the current workthe model is capable of producing the desired results, andillustrate them graphically. These can then be used tomonitor hole cleaning performance during drilling operations.However there is still the need to validate the application ofthe model with field data, and benchmark with other industrymodels.Future Work• Field application to test the accuracy of the model;• Fully integration into computer package to work with rig instrumentation;• Further laboratory experiment to prove the application of all the concepts presented into the project.
REFERENCES1. Cayeux, E., Mesagan, T., Tanripada, S., Zidan, M., & Fjelde, K. K. .Real-Time Evaluation of Hole-Cleaning Conditions With a TransientCuttings-Transport Model. Society of Petroleum Engineers 2014;(SPE163492): . doi:10.2118/163492-PA (accessed June 2015).2. K&M, Extended Reach Engineering Design and ImplementationCourse-Complex Directional Wells.. [Training Material]. K&MTechnology Group. October 17, 2011.
Figure 2. Forces acting on a suspended cutting.(1)
Figure3. Cuttings transport at various angle.(2)
METHODOLOGYThe model is made up three major modules that are relatedto the different stages of the hole cleaning. The first stage isthe design stage (determination of flow rate, pipe rotation,ECD, SPP, Torque and Drag, and Cuttings volume), thesecond stage is the real-time data(comparing the real timedata with the estimated values), and the final stage is thedecision making where actions are taken when the real dataand the estimated do not match.The steps to create the model are:• Literature review on the current work of hole cleaning;• Literature review of models of cuttings concentration in the well;• Review of hydraulic optimisation for hole cleaning;• Analysis of the factors that affect hole cleaning;• Review of the indicators of poor hole cleaning during drilling;• Build the concept of the model • Interaction of data from the major areas of the model;• Assessment of the results of the model and conclusion.
Figure4. Annular cross sectional view of a high angle well(65°+). (2)Figure 1. Hole cleaning optimisation model
