Optimization of Flow Rate and Pipe Rotation Speed Considering Effective Cuttings Transport Using Data-Driven Models

Effectively transporting drilled cuttings to the surface is a vital part of the well construction process. Usually, mechanistic models are used to estimate the cuttings concentration during drilling. Based on the results from these model, operational parameters are adjusted to mitigate any nonproductive time events such as pack-off or lost circulation. However, these models do not capture the underlying complex physics completely and frequently require updating the input parameters, which is usually performed manually. To address this, in this study, a data-driven modeling approach is taken and evaluated together with widely used mechanistic models. Artificial neural networks are selected after several trials. The experimental data collected at The University of Tulsa–Drilling Research Projects (in the last 40 years) are used to train and validate the model, which includes a wide range of wellbore and pipe sizes, inclinations, rate-of-penetration values, pipe rotation speeds, flow rates, and fluid and cuttings properties. It is observed that, in many cases, the data-driven model significantly outperforms the mechanistic models, which provides a very promising direction for real-time drilling optimization and automation. After the neural network is proven to work effectively, an optimization attempt to estimate flow rate and pipe rotation speed is introduced using a genetic algorithm. The decision is made considering minimizing the required total energy for this process. This approach may be used as a design tool to identify the required flow rate and pipe rotation speed to acquire effective hole cleaning while consuming minimal energy

Estimation of Hardgrove grindability index of Turkish coals by neural networks

In this research, different techniques for the estimation of coal HGI values are studied. Data from 163 sub-bituminous coals from Turkey are used by featuring I I coal parameters, which include proximate analysis, group maceral analysis and rank. Nonlinear regression and neural network techniques are used for predicting the HGI values for the specified coal parameters. Results indicate that a hybrid network which is a combination of 4 separate neural networks gave the most accurate HGI prediction and all of the neural network models, outperformed non-linear regression in the estimation process

Experimental investigation of hydrate formation, plugging and flow properties using a high-pressure viscometer with helical impeller

Abstract Slurry transport has become a subject of interest in several industries, including oil and gas. The importance of slurry/solid transport in the oil and gas industry is evident in areas of cuttings transport, sand transport and, lately, hydrates. Hydrate formation, if not properly monitored and controlled, may lead to pipeline blockage. To avoid pipeline blockage and other hydrate formation risks, chemical additives are added to the system. Additives such as anti-agglomerants help improve hydrate transportability by dispersing the formed hydrates into slurries and preventing them from sticking to the pipe wall. This enables transportation of highly concentrated slurries. However, the high hydrate volume fractions (HVF) slurries may exhibit complex rheology. There is therefore a great need to correlate flow properties such as friction factor and viscosity to HVF. Hydrate slurry transport is important whether hydrates are deliberately generated for energy storage purposes or hydrates formed because of the prevailing flow conditions. However, when determining the viscosity of a fluid containing solid particles, the conventional viscometer types such as concentric cylinders and cone and plate are often not suitable. This is because either the narrow gap would not accommodate the particle size or their inability to maintain the particles suspended leading to bed formation. In this work, a high-pressure mixer-type viscometer was used to generate and characterize hydrate slurries. This work aims to generate a significant amount of hydrate slurry characterization data that may be used as basis for better rheometer designs, hydrate slurry flow properties modeling or integration of hydrate transportability into general multiphase modeling. Results showed that intermediate watercuts posed the greatest pipeline plugging risk for all the oils tested. The amount of transportable hydrates increased with oil viscosity. Generally, hydrate slurries generated exhibited shear thinning behavior that increased with increasing hydrate volume fraction. However, the overall rheology of these slurries is a complex function of the oil used, watercut, gas added to the system and hydrate solid fraction. Lowering shear rates for high HVF systems resulted in separation. Results in this work further suggest that hydrate transportation may be possible with minimum risk if anti-agglomerants are used and high enough shear is applied. On the other hand, if no anti-agglomerant is used, severe aggregation may result in flow line plugging

Modeling and Experimental Study of Newtonian Fluid Flow in Annulus

A major concern in drilling operations is the proper determination of frictional pressure loss in order to select a mud pump and avoid any serious problems. In this study, a mechanistic model is proposed for predicting the frictional pressure losses of light drilling fluid, which can be used for concentric annuli. The experimental data that were available in the literature and conducted at the Middle East Technical University-Petroleum Engineering (METU-PETE) flow loop as well as computational fluid dynamics (CFD) software are used to verify the results from the proposed mechanistic model. The results showed that the proposed model can estimate frictional pressure losses within a +/- 10% error interval when compared with the experimental data. Additionally, the effect of the pipe eccentricity on frictional pressure loss and tangential velocity using CFD for laminar and turbulent flow is also examined. It has been observed that pipe eccentricity drastically increases the tangential velocity inside the annulus; especially, the flow regime is turbulent and frictional pressure loss decreases as the pipe eccentricity increases. [DOI: 10.1115/1.4002243

Friction factors for hydraulic calculations considering presence of cuttings and pipe rotation in horizontal/highly-inclined wellbores

Pressure loss calculations have a vital role for determining hydraulic horsepower requirements and to predict bottomhole treating pressure. One of the major concerns in developing hydraulic programs is to estimate the frictional pressure losses while cuttings are present in the annulus during pipe rotation. An experimental work has been carried out in a cuttings transport flow loop capable of operating at various inclinations. The pressure drop in the test section was recorded for variable flow rates, cuttings concentrations, pipe inclinations and rotation speeds. Existence of cuttings increase the pressure drop due to decrease in flow area inside the wellbore. As there are cuttings in the system, pipe rotation decreases the frictional pressure loss considerably in particular if the pipe is making an orbital motion in the eccentric annulus. Cuttings bed thickness defined as the ratio of cuttings bed area to the wellbore area is expressed in terms of dimensionless parameters obtained from dimensional analysis. Empirical expressions and charts for friction factor are proposed for low and high viscosity fluids in terms of combined Reynolds number and stationary cuttings bed thickness

Analysis of the influence of bubble size and texture on foam characterization

Foam is one of the most frequently-used lightened fluids in underbalanced drilling applications. However, the rheological characterization of foam remains a difficult and challenging task largely due to problems associated with problems associated with the accurate determination of rheological parameters. Foam flow tests were conducted using an experimental flow loop which consisted of a set of smooth pipes of various diameters. Foams generated from different surfactants and different generation techniques were characterized from the texture and bubble size point of view using digital image processing. This paper outlines the approach taken to relate the foam rheological parameters obtained from the flow loop tests with its bubble size and texture. © BHR Group 2005 Multiphase Production Technology 12

Support Vector Regression and Computational Fluid Dynamics Modeling of Newtonian and Non-Newtonian Fluids in Annulus With Pipe Rotation

The estimation of the pressure losses inside annulus during pipe rotation is one of the main concerns in various engineering professions. Pipe rotation is a considerable parameter affecting pressure losses in annulus during drilling. In this study, pressure losses of Newtonian and non-Newtonian fluids flowing through concentric horizontal annulus are predicted using computational fluid dynamics (CFD) and support vector regression (SVR). SVR and CFD results are compared with experimental data obtained from literature. The comparisons show that CFD model could predict frictional pressure gradient with an average absolute percent error less than 3.48% for Newtonian fluids and 19.5% for non-Newtonian fluids. SVR could predict frictional pressure gradient with an average absolute percent error less than 5.09% for Newtonian fluids and 5.98% for non-Newtonian fluids

Experimental Study of Single Taylor Bubble Rising in Stagnant and Downward Flowing Non-Newtonian Fluids in Inclined Pipes

An experimental investigation of single Taylor bubbles rising in stagnant and downward flowing non-Newtonian fluids was carried out in an 80 ft long inclined pipe (4°, 15°, 30°, 45° from vertical) of 6 in. inner diameter. Water and four concentrations of bentonite–water mixtures were applied as the liquid phase, with Reynolds numbers in the range 118 Re E0) ranging from 3212 to 3405 and apparent viscosity (μapp) ranging from 0.001 Pa∙s to 129 Pa∙s. The proposed correlation exhibits good performance for predicting drift velocity from both the present study (mean absolute relative difference is 0.0702) and a database of previous investigator’s results (mean absolute relative difference is 0.09614)

An integrated fluid flow and fracture mechanics model for wellbore strengthening

Fracture-based wellbore strengthening techniques are preventive methods that can reduce the cost of lost circulation and non-productive time. The mud weight window can be extended by plugging fractures with wellbore strengthening materials (WSM) in the near-wellbore region. To maximize the strengthening effect, accurate fracture geometry prediction is of critical importance to the design of WSM. This paper presents a novel, coupled fluid flow and fracture mechanics model for wellbore strengthening applications that accounts for near-wellbore-induced fracture behavior. For fluid flow, mass conservation is considered and momentum conservation is examined; the latter shows that pressure loss with near-wellbore fracturing is low. Thus, we can neglect the pressure drop in the fractures and assume the fluid pressure inside the fractures is equal to the wellbore pressure. The pressure-width relationship (rock elastic deformation) and stress intensity factor are obtained by a dislocation-based approach. For the fracture propagation criterion, the calculated stress intensity factor is compared with fracture toughness at each time step. The stress intensity factor and fracture reopening pressure (FROP) are verified with Tada's model and Feng's model, respectively. Then, simulation results are compared with the large leak-off solutions of the Perkins-Kern-Nordgren (PKN) fracture model. The simulation results reveal that the PKN model overestimates the fracture mouth width, fracture length, and wellbore pressure. Furthermore, the simulation results of wellbore pressure show a different trend. Therefore, we cannot directly use the PKN model to design wellbore strengthening applications. The main reason is the presence of wellbore can generate near-wellbore effects that cannot be disregarded. Finally, we conduct a comprehensive parametric study (i.e., fracture toughness, Young's modulus, Poisson's ratio, horizontal stress ratio, and permeability) on wellbore strengthening fracturing. The proposed model is useful for wellbore strengthening applications using the intentionally induced fractures (i.e., near-wellbore fracturing). Particle size distribution (PSD) of WSM can be designed based on the simulated fracture geometry. No complex model mesh generation or assignment of boundary conditions are needed, which are commonly used in finite element simulation or other numerical methods. The proposed model can also be used to optimize wellbore strengthening operations by performing sensitivity analysis