Confidence in Critical Velocity Predictions for Solids Transport

Abstract

Sand is often produced with oil and gas even though sand control practices are used. To successfully transport solids in pipelines, the fluid velocity must exceed the critical velocity. Solids transport models are used to predict this velocity. However, for the same input field or laboratory condition, the models' critical velocity predictions may differ by orders of magnitude. Furthermore, none of the models provide information regarding the confidence in their velocity predictions. This paper introduces a systematic methodology, which selects the appropriate solids transport models for predicting the operational critical velocity envelope to ensure solids transport in the pipe to within a predetermined confidence level. Given a field or laboratory condition as input, the approach generates: (1) velocity predictions and uncertainty bounds of all models to within a predetermined confidence level, (2) recommendation of appropriate models for calculating the critical velocity at the input condition, and (3) impact of the uncertainty of input condition, experimental data, and model on the overall uncertainty bounds. The methodology uses data clustering, model evaluation, optimization, and uncertainty propagation approaches. Based on three Case Studies, the velocity envelopes suggested by the methodology, at the 90% confidence level, are consistent with experimental observations. For input laboratory conditions, which are used for validation purposes, the contributions of model, input condition, and experimental data uncertainties to the velocity prediction uncertainty were between 50 -90%, 3 -20%, and 6 -40%, respectively. If the parameters of the selected models were fine-tuned, for the same input conditions, the above uncertainties contribute about 40 -90%, 4 -15%, and 1 -50%, respectively, to the velocity prediction uncertainty. For an input field condition (the fourth Case Study), the above values become about 35 -70%, 7 -25%, and 25 -45%, respectively; and about 25 -30%, 30 -32%, and 40 -42%, respectively, if the parameters of the models are fine-tuned prior to uncertainty estimation. The results of these Case Studies suggest that for laboratory conditions, most of the uncertainty in a model's critical velocity prediction comes from the model, while for field conditions, the uncertainties of the model, input condition, and data may have nearly equal contributions.

Mechanical Impurities Carry-Over from Horizontal Heavy Oil Production Well

“…In fact, there are more than 60 models that describe the behavior of particles in the flow [10], among the main ones stand out: the model proposed in 1980, Oroskar and Turian [11], the model of Salama (1998) [12], Danielson (2007) [13], Davies (1987) [14].…”

An experimental study of coal-fines migration in Coalbed-methane production wells

“…Typically, these solids transportation models take the independent variables (particle volumetric concentration, inclination angle of the pipe, fluid density and viscosity, particle density and diameter, and hydraulic diameter of the pipe) as inputs, and generate the critical velocity as output. A review of the literature reveals that there are more than 50 solids transportation models that can be used to predict the critical velocity (Soepyan et al, 2014). Although some of the literature presented researches on sand migration in wellbore, none of the theory is appropriate for coal fines transportation in wellbore because: the size of coal fine is substantially tiny; the particle shape is irregular comparing to the round shape of sand; the flow in rod pumping wells is intermittent comparing to continuous flow in pipeline, the buoyance is much significant.…”

Modeling Results for the Real Horizontal Heavy-Oil-Production Well of Mechanical Solids

“…Worldwide, there are more than 60 models [26] describing the behavior of particles in the flow. The high number of works is attributable to the fact that the task of solids transfer and deposition is extremely complex and multifaceted.…”