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Hydrate bedding is defined as the gravitational segregation of hydrate particles, leading to their accumulation at the bottom of the pipe. Previous research has shown that hydrate bedding is a phys...

An optimally designed nozzle can be used as an efficient artificial lift system to deliquify gas wells. The objective of this work is to determine the most optimum nozzle parameters and geometry that would maximize critical pressure ratio while minimizing pressure drop across the nozzle under two-phase flow conditions. Six optimum nozzle geometries, evaluated under single-phase flow conditions in a previous study, are evaluated in this work. Two separate facilities were used to conduct the two-phase (air and water) experiments: a horizontal facility with 1.5 in. inner diameter (ID) PVC pipelines and a 30 ft long lateral pipeline section, and a vertical facility with 1.5 in. ID PVC pipelines and a 30 ft long vertical pipeline section. The horizontal facility was used to study the effect of introducing water into the system as a second phase, and the vertical facility was used to simulate conditions of a gas well with a nozzle installed as an artificial lift system. Horizontal flow experimental results showed that critical pressure ratio decreases for two-phase flow relative to single-phase flow. The distance of the annular churn flow pattern observed downstream the nozzle may be related to the nozzle performance; significantly lower performance was observed for the LJ nozzle in two phase horizontal testing relative to other nozzles – one characteristic this might be attributed to is the peculiarly longer distance of downstream annular churn flow pattern observed for this particular nozzle compared to other nozzles. Based on data analysis, the ASTAR nozzle group showed the most improved performance, similar to results obtained in single-phase horizontal testing. Based on vertical experimental results, the most optimum nozzle geometry to deliquify a loaded gas well was identified as the ASTAR nozzle 2, a parabolic nozzle geometry. A significant temperature drop downstream the nozzle was observed during these experiments. It is important to account for temperature change while designing a nozzle in order to avoid flow assurance problems, such as gas hydrate formation. The trends observed in relative performance between different nozzle geometries (rankings based on critical pressure ratio and pressure drop) for two-phase vertical experiments were similar to those observed for single-phase horizontal experiments. Therefore, single-phase experiments could be sufficient to evaluate relative nozzle geometry performance based on critical pressure ratio, for the conditions used in this study.

The high pressure and low temperature operational conditions of deepwater subsea facilities often result in the formation of gas hydrates, which is one of the most challenging flow assurance issues. The variant water cuts and flowline geometries could result in complicated flow patterns leading to different hydrate formation mechanisms. In previous work, we have developed hydrate formation models both for oil- and water-dominated systems. The model for oil-dominated systems considers the water phase being dispersed as droplets in an oil continuous layer, and uses either a kinetics or a transport model to calculate hydrate formation at the interface of water droplets. On the other hand, water-dominated systems contain small amounts of oil, and a mass transfer-based hydrate growth model is used. This paper presents a new transient hydrate formation model that predicts hydrate growth and transportability in oil- and water-dominated environments, which might be present simultaneously in oil and gas pipelines due to changes in fluid distribution in complex multiphase flow systems. Simulations of high-pressure pilot-scale flowloop experiments at different water cuts are used to verify this modeling approach. Furthermore, the proposed hydrate simulation tool is applied to analyze the flow dynamics of a subsea tieback involving hydrate formation at varying water cuts after flowloop verification. This simulation model is targeted to be widely used to simulate oil-dominated pipelines, as well as high water cut systems leading to phase inversions, and represents a step further towards the development of more comprehensive hydrate formation models.

Fractured enhanced geothermal system (EGS) reservoirs are typically sensitive to thermal and mechanical change induced by cold water injection. It has been observed that the permeability at the cold water injector is significantly enhanced. The physical thermal-hydrologic-mechanic (THM) process behind this phenomenon is that, the injection of cold water decreases the temperature of the reservoir rock and causes the matrix block to shrink, resulting in an increase of the fracture aperture and fracture permeability. Therefore, it is of great importance to quantify the effect of thermally induced fracture aperture change to better predict the behavior/performance of EGS reservoirs. In this work, we develop a novel correlation of the thermal-induced normal change of fracture aperture. The new correlation is based on the analytical solution of the governing displacement equations. Compared to the existing empirical correlations, the new correlation can better describe the physical processes by including the thermal effect on the matrix-fracture deformation. We have verified this correlation with respect to refined simulation results and implemented this correlation in a fully coupled massively parallel geothermal simulator, THM-EGS. We have applied this correlation to study field scale problems with certain parameters from Habanero Field in Copper Basin, Australia. Our results demonstrate that the fracture permeability near the cold water injector could be enhanced 7 times.

As industry moves toward the production of oil and gas resources in deep offshore environments, the prospective formation of natural gas hydrates under low temperature, high-pressure conditions poses an increasing risk of pipeline blockage. Successful management of this risk requires a precise forecast of the hydrate growth rate. Such predictions should incorporate quantitative descriptions of both deterministic and probabilistic hydrate phenomena. In this work, we present a first step towards such a quantitative risk assessment for systems that form hydrate slurries, based on a consideration of the stochastic nature of hydrate formation. Our framework introduces a new approach to risk assessment, by coupling a laboratory-derived probabilistic nucleation model with existing deterministic calculations for hydrate slurry viscosification. This new approach is used to extend a previously-described hydrate risk algorithm, the Hydrate Flow Assurance Simulation Tool (HyFAST), which enables the rapid assessment of hydrate slurry viscosification using the most advanced models available. Importantly, while the previous version of HyFAST was constrained to calculations in flowloop and autoclave geometries, for which it is sufficient to consider a single volume element, the new version of the HyFAST algorithm allows calculations for flowlines wherein a series of multiple volume elements are considered. The advanced hydrate formation models within this algorithm allow identification of critically important hydrate formation scenarios, and may serve as a screening tool for cases that then require study within rigorous hydrodynamic packages such as OLGA® or LedaFlow® to examine behaviour during key transient events. By coupling the outputs of our predictive algorithm and quantitative risk framework, we demonstrate a new capability to assess what constitutes an acceptable level of hydrate formation. We use this algorithm in a series of case studies that compare the effectiveness of common hydrate mitigation strategies over the life of a reservoir, including the optimization of a wellhead choke opening for both production rate and hydrate blockage risk.

The formation and accumulation of natural gas hydrates in deep subsea flow lines are one of the most challenging flow assurance problems. Typical high pressure/low temperature operation conditions in deep subsea facilities promote rapid formation of gas hydrates. Recent observations in flow loop experiments in gas/water systems suggested a relationship between hydrate volume and flow regime on pressure drop. In the current work, a simple hydrodynamic slug flow model, based on fundamental multiphase flow concepts, is coupled with a transient hydrate kinetics model to study the effect of hydrate formation on slug flow in gas/water systems.

As oil/gas subsea fields mature, the amount of water produced increases, which results in an increased risk of gas hydrate plug formation in the flowlines. It is important to understand the mechanism of gas hydrate plug formation in high water cut systems in order to manage gas hydrate risk. In this work, we performed an extensive series of gas hydrate formation and dissociation experiments in a 4-inch diameter flowloop at the ExxonMobil research facility at Friendswood, TX. The flowloop was instrumented for pressure, temperature, density, and differential pressure measurements. The effect of mixture velocity (1–2.5 m/s) and liquid loading (50–90 vol.%) on gas hydrate plug formation was studied for 100 vol.% water cut (no oil present) systems, with methane as the gas hydrate former. The pressure drop across the pump due to flow did not substantially increase until a certain concentration of gas hydrates, defined as ϕ transition , formed; this transition, as measured by the rapid increase in pressure drop, can be used as an indication for onset of hydrate plug formation. ϕ transition was found to be unaffected by liquid loading and the presence of salt (3.5 wt.% NaCl) in water, while it increased with increasing mixture velocity. A gas hydrate plugging mechanism for 100 vol.% water cut systems is proposed, which involves a transition from homogeneous to heterogeneous suspensions of gas hydrate particles in water. We hypothesize that the large pressure drop observed after ϕ transition results from the formation of a gas hydrate bed and wall deposit. A correlation between ϕ transition and the mixture velocity is presented, this correlation allows the prediction of an onset of hydrate plug formation based on the fluids mixture velocity.

After conventional waterflooding processes the residual oil in the reservoir remains as a discontinuous phase in the form of oil drops trapped by capillary forces and is likely to be around 70% of the original oil in place (OOIP). The EOR method so-called Alkaline–Surfactant–Polymer (ASP) flooding has been proved to be effective in reducing the oil residual saturation in laboratory experiments and field projects through reduction of interfacial tension and mobility ratio between oil and water phases. A critical step for the optimal design and control of ASP recovery processes is to find the relative contributions of design variables such as, slug size and chemical concentrations, in the variability of given performance measures (e.g., net present value, cumulative oil recovery), considering a heterogeneous and multiphase petroleum reservoir (sensitivity analysis). Previously reported works using reservoir numerical simulation have been limited to local sensitivity analyses because a global sensitivity analysis may require hundreds or even thousands of computationally expensive evaluations (field scale numerical simulations). To overcome this issue, a surrogate-based approach is suggested. Surrogate-based analysis/optimization makes reference to the idea of constructing an alternative fast model (surrogate) from numerical simulation data and using it for analysis/optimization purposes. This paper presents an efficient global sensitivity approach based on Sobol's method and multiple surrogates (i.e., Polynomial Regression, Kriging, Radial Base Functions and a Weighed Adaptive Model), with the multiple surrogates used to address the uncertainty in the analysis derived from plausible alternative surrogate-modeling schemes. The proposed approach was evaluated in the context of the global sensitivity analysis of a field scale Alkali–Surfactant–Polymer flooding process. The design variables and the performance measure in the ASP process were selected as slug size/concentration of chemical agents, and cumulative oil recovery, respectively. The results show the effectiveness and efficiency of the proposed approach since it allows establishing the relative contribution of the design variables (main factors and interactions) to the performance measure variability using a limited number of computationally expensive reservoir simulations.

After conventional waterflood processes the residual oil in the reservoir remains as a discontinuous phase in the form of oil drops trapped by capillary forces and is likely to be around 70% of the original oil in place (OOIP). The EOR method socalled alkaline–surfactant–polymer (ASP) flooding has proved to be effective in reducing the oil residual saturation in laboratory experiments and field projects through the reduction of interfacial tension and mobility ratio between oil and water phases. A critical step to make ASP floodings more effective is to find the optimal values of design variables that will maximize a given performance measure (e.g., net present value, cumulative oil recovery) considering a heterogeneous and multiphase petroleum reservoir. Previously reported works using reservoir numerical simulation have been limited to sensitivity analyses at core and field scale levels because the formal optimization problem includes computationally expensive objective function evaluations (field scale numerical simulations). This work presents a surrogate-based optimization methodology to overcome this shortcoming. The proposed approach estimates the optimal values for a set of design variables (e.g., slug size and concentration of the chemical agents) to maximize the cumulative oil recovery from a heterogeneous and multiphase petroleum reservoir subject to an ASP flooding. The surrogate-based optimization approach has been shown to be useful in the optimization of computationally expensive simulation-based models in the aerospace, automotive, and oil industries. In this work, we improve upon this approach along two directions: (i) using multiple surrogates for optimization, and (ii) incorporating an adaptive weighted average model of the individual surrogates. The cited approach involves the coupled execution of a global optimization algorithm and fast surrogates (i.e., based on Polynomial Regression, Kriging, Radial Basis Functions and a Weighted Average Model) constructed from field scale

Typically, the optimization of oil production systems is conducted as a non-systematic effort in the form of trial and error processes for determining the com- bination of variables that leads to an optimal behavior of the system under consideration. An optimal or near opti- mal selection of oil production system parameters could significantly decrease costs and add value. This paper presents a solution methodology for the optimization of integrated oil production systems at the design and oper- ational levels, involving the coupled execution of simul- ation models and optimization algorithms (SQP and DIRECT). The optimization refers to the maximization of performance measures such as revenue present value or cumulative oil production as objective functions, and tub- ing diameter, choke diameter, pipeline diameter, and oil flow rate as optimization variables. The reference con- figuration of the oil production system includes models for the reservoir, tubing, choke, separator, and business economics. The optimization algorithms Sequential Quadratic Programming (SQP) and DIRECT are con- sidered as state-of-the-art in non-linear programming and global optimization methods, respectively. The proposed solution methodology effectively and efficiently optimizes integrated oil production systems within the context of synthetic case studies, and holds promise to be useful in more general scenarios in the oil industry.