A Practical Method of Predicting Calcium Carbonate Scale Formation in Well Completions
- Syed Hamid (Halliburton) | Orlando De Jesús (Consultant) | Carlos Jacinto (Petrobras) | Ronaldo Izetti (Petrobras) | Hardy Pinto (Petrobras) | Enrique Droguett (University of Maryland) | Christopher Edwards (Halliburton) | Juanita Cassidy (Halliburton) | Haoyue Zhang (Halliburton) | Pete Dagenais (Halliburton) | Marcelo A. P. Batocchio (Welltec)
- Document ID
- Society of Petroleum Engineers
- SPE Production & Operations
- Publication Date
- February 2016
- Document Type
- Journal Paper
- 1 - 11
- 2016.Society of Petroleum Engineers
- interval control valve, presalt well, intelligent well completion, rate of scale formation, prediction of tool performance
- 10 in the last 30 days
- 660 since 2007
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Scale formation in downhole tubular-flow passages can cause partial to complete plugging that will affect production or injection rates adversely. In an intelligent-well completion in which the interval-control-valve (ICV) opening must be changed to control flow rate, the completion will become ineffective if plugging of clearances prevents valve actuation. To mitigate these problems, a method to predict the potential rate of scale formation under realistic conditions has been developed.
This empirical method allows prediction of tool performance under scale-forming conditions for downhole applications, and uses chemical data and flow fields generated by computational-fluid-dynamics (CFD) models for downhole tools. Chemical data are obtained from laboratory tests on coupons by use of brines matching the chemistry of connate fluids. Tests were conducted in a high-pressure, corrosion-resistant vessel over a range of high pressures (100 to 10,000 psi) and high temperatures (75 to 150°C) to simulate downhole well conditions. Two test sets were conducted, each with fluid at rest and with an impeller generating low velocity in the reaction vessel, ranging from 4 hours to 4 days, with scaling rates determined from coupon-weight gain. Concentrations in the range of 50 to 125% of the typical connate-fluid concentration were used.
The weight-gain data obtained from the coupon tests and from a tube-plugging test were used to develop an empirical model for scale-growth rate at a given point on a solid surface with pressure, pressure gradient, temperature, fluid velocity, and brine concentration as independent variables. Artificial-intelligence methodology was used to develop this model, which can be used to predict scale-growth rate for any arbitrary geometry. By use of the internal geometry of any tool to be modeled, a CFD model is prepared and the pressure, fluid velocity, and pressure-gradient data are generated for the entire internal solid surface of the tool for a given flow rate through the tool. These data are fed into the empirical model to calculate the scale-growth rate, which is integrated to obtain scale thickness at each point of the internal solid boundary. To verify accuracy, scale formation in a 4.5-in. ICV was predicted at high-pressure, high-temperature conditions at a low flow rate. Laboratory tests on the valve matched the model predictions well enough, which enabled Petrobras to design a better completion and fluid-handling system for a presalt well.
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