New Technology to Evaluate Equivalent Circulating Density While Drilling Using Artificial Intelligence
- Mahmoud Elzenary (King Fahd University of Petroleum & Minerals) | Salaheldin Elkatatny (King Fahd University of Petroleum & Minerals) | Khaled Z. Abdelgawad (King Fahd University of Petroleum & Minerals) | Abdulazeez Abdulraheem (King Fahd University of Petroleum & Minerals) | Mohamed Mahmoud (King Fahd University of Petroleum & Minerals) | Dhafer Al-Shehri (King Fahd University of Petroleum & Minerals)
- Document ID
- Society of Petroleum Engineers
- SPE Kingdom of Saudi Arabia Annual Technical Symposium and Exhibition, 23-26 April, Dammam, Saudi Arabia
- Publication Date
- Document Type
- Conference Paper
- 2018. Society of Petroleum Engineers
- 2 in the last 30 days
- 91 since 2007
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The equivalent circulation density (ECD) is a very important parameter in drilling high pressure high temperature (HPHT) wells and deep water wells. In formations where the margins between the formation pore pressure (PP) and the formation fracture pressure (FP) is narrow, ECD is a key parameter. In these critical operations, the ECD is used to control the formation pressure and prevent kicks. The recent approaches in oilfield depend mainly on using expensive downhole sensors for providing real time values of ECD. These tools also have operational limits which may prevent using it in all downhole conditions.
The objective of this paper is to present a new technique for predicting ECD values while drilling without the need for downhole tools. The technique uses surface drilling parameters in a model to evaluate the ECD values precisely using artificial intelligence (AI) techniques. The model was developed using two AI techniques; artificial neural network (ANN) and adaptive neuro fuzzy inference system (ANFIS). Using this technique will save cost and time by eliminating needs for using expensive, complicated downhole tools like measurement while drilling (MWDs) and pressure while drilling (PWD).
The results obtained showed that the accuracy of the developed model is very high with error factor less than 0.22 % comparing the actual to predicted ECD values. Implementing this model in well design will have great impact in accurately choosing correct mud weights to safely drill the well. It will also minimize the drilling problems related to ECD such as losses or gains especially in critical area where margins between pore and fracture pressure is very narrow.
In most HPHT and deep water wells, the margins between the formation pore pressure (PP) and the formation fracture pressure (FP) is narrow; and here appears the importance of evaluating correct ECD values. Actually in these critical operations, the ECD is used to control the formation pressure and prevent kicks. When the pumps are switched off, the loss of ECD may result in underbalanced conditions. In same time, it is not possible to increase the mud weight due to fracture pressure limitations. Here we find also the implementation of continuous circulating system (CCS) tools which allows for the connection to be performed while pumps are on; in order to keep ECD values controlling the formation pressure (Barantho et al. 1995; Ataga et al. 2012).
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