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Results
Abstract Asphaltic and sand production problems are common production challenges in the petroleum industry. Asphaltic problem results from the depositions of heavy material (asphaltene) in the vicinity of the well which may cause severe formation damage. Asphaltic materials are expected to deposit in all type of reservoirs. Sand production refers to the phenomenon of solid particles being produced together with the petroleum fluids. These two problems represent a major concern in oil and gas production systems either in the wellbore section or in the surface treatment facilities. Production data, well logging, laboratory testing, acoustic, intrusive sand monitoring devices, and analogy are different techniques used to predict sand production. This paper introduces a new technique to predict and quantify the skin factor resulting from asphaltene deposition and/or sand production using pressure transient analysis. Pressure behavior and flow regimes in the vicinity of horizontal wellbore are extremely influenced by this skin factor. Analytical models for predicting this problem and determining how many zones of the horizontal well that are affected by sand production or asphaltic deposition have been introduced in this study. These models have been derived based on the assumption that wellbore can be divided into multi-subsequent segments of producing and non-producing intervals. Producing intervals represent free flowing zones while non producing intervals represent zones where perforations are closed because of sand or asphaltic deposits. The effective length of the segments of a horizontal well where sand and/or asphaltene are significantly closing the perforations can be calculated either from the early radial or linear flow. Similarly, the effective length of the undamaged segments can be determined from these two flow regimes. The numbers of the damaged and undamaged zones can be calculated either from the intermediate radial (secondary radial) or linear flow if they are observed. If both flow regimes are not observed, the zones can be calculated using type curve matching technique. The paper will include the main type-curves, step-by-step procedure for interpreting the pressure test without using type curve matching technique when all necessary flow regimes are observed. A step-by-step procedure for analyzing pressure tests using the type-curve matching technique will also be presented. The procedure will be illustrated by several numerical examples.
- North America > United States (1.00)
- Asia (0.68)
- Europe > Norway (0.67)
- Geology > Rock Type > Sedimentary Rock > Clastic Rock (0.46)
- Geology > Geological Subdiscipline > Geomechanics (0.46)
Abstract Sand production is one of the more critical issues causing delays and high costs to the petroleum production industry. To measure solid production in the hydrocarbon stream a number of sand monitors have been developed. Such monitors are installed in the flow line and are intended to provide information such as the onset of solid production or the amount of produced solids. Most sand monitors are based on the measurement of erosion due to impingement of sand particles or measuring ultrasonic signals generated by particle impacts on the pipe wall or piezoelectric elements. Having described the principal behind available monitors in the industry, capabilities and limitation of each type is explained in Part 1. Part 2 is comprised of a literature review carried out on the techniques which have the potential to be utilised in new generations of solids monitors. The principles of such methods as well as their advantages and disadvantages for solids monitoring applications are mentioned. In Part 3 subjects such as improving the data quality and data interpretation of current techniques, integration of available techniques into a single piece of equipment, and ranking of the most promising cases which are worthy of further investigation are discussed.
- Europe (1.00)
- North America > United States > Texas (0.28)
- Overview (0.48)
- Research Report (0.47)
Experimental Study on Natural Gas Hydrate Slurry Flow
Lv, X. F. (China University of Petroleum-Beijing) | Gong*, J.. (China University of Petroleum-Beijing) | Li, W. Q. (China University of Petroleum-Beijing) | Shi, B. H. (China University of Petroleum-Beijing) | Yu, D.. (China University of Petroleum-Beijing) | Wu, H. H. (China University of Petroleum-Beijing)
Abstract To better understand hydrate slurry flow, a series of experiments have been performed, including water, natural gas and diesel oil, under 4MPa (system pressure), 40Hz (initial pump speed). The experiments have been conducted in a high-pressure hydrate flow loop newly constructed in China University of Petroleum (Beijing), and dedicated to flow assurance studies. A Focused Beam Reflectance Measurement (FBRM) is installed in this flow loop, which provides a quantitative chord length distribution (CLD) of the particles/droplets in the system. Firstly, the influence of flow rate on the hydrate slurry flow was discussed. Then we have studied the factors such as water-cut and additive dosage on the hydrate induction period and the CLD before/after hydrate formation. Finally, we have fitted a new correlation between the dimensionless rheological index, n′, and water-cut as well as additive dosage, according to these experimental results. And a laminar flow pressure model of quasi-single phase hydrate slurry has been established in this paper.
- North America > United States > Texas (0.46)
- Asia > China > Beijing > Beijing (0.25)
- Research Report > Experimental Study (0.64)
- Research Report > New Finding (0.50)
Abstract This paper presents the results of a modeling study for paraffin deposition under single-phase turbulent flow conditions. Analysis on flow loop deposition data is presented for various crude oils such as South Pelto crude oil, Garden Banks condensate and Trans Alaska Pipeline System (TAPS) crude oil. A new closure relationship simulating shear effects is proposed. The experimental data were obtained under single-phase turbulent flow conditions using different types of crude oils on different test facilities at TUPDP (Tulsa University Paraffin Deposition Projects). These data were used to develop a correlation which can be used to predict the relative difference between the estimated wax mass deposition rate and mass diffusion rate from Fick's law as a function of the Nusselt and Sherwood numbers representing the heat and mass transfer characteristics under turbulent flow conditions. Uncertainty analysis was conducted on this correlation and most of the data points fall within the range of ±25%. Model predictions have been compared using a film mass transfer model and equilibrium model. It is observed that the film mass transfer model always over predicts the deposition rate. But the equilibrium model can both under predicts and over predicts the deposition rate. The results presented in this paper can be used to improve the accuracy of paraffin deposition model predictions under turbulent flow conditions.
- North America > United States > Texas (0.28)
- North America > United States > Alaska (0.24)
- Europe > Norway > North Sea > Northern North Sea > North Viking Graben > PL 054 > Block 31/6 > Troll Field > Sognefjord Formation (0.99)
- Europe > Norway > North Sea > Northern North Sea > North Viking Graben > PL 054 > Block 31/6 > Troll Field > Heather Formation (0.99)
- Europe > Norway > North Sea > Northern North Sea > North Viking Graben > PL 054 > Block 31/6 > Troll Field > Fensfjord Formation (0.99)
- (9 more...)
- Production and Well Operations > Well & Reservoir Surveillance and Monitoring > Production logging (1.00)
- Production and Well Operations > Production Chemistry, Metallurgy and Biology > Inhibition and remediation of hydrates, scale, paraffin / wax and asphaltene (1.00)
- Facilities Design, Construction and Operation > Flow Assurance > Precipitates (paraffin, asphaltenes, etc.) (1.00)
Abstract In 2010, as part of the remediation efforts surrounding the Deepwater Horizon drilling rig incident, also known as the Macondo incident, multiple containment and collection systems were deployed in an attempt to capture as much oil as possible, as well as minimizing the amount of oil released into the Gulf of Mexico. The Top Hat was one of the recovery systems implemented to collect oil. In a Top Hat recovery system, oil is produced up the tubing and hot water is injected down an annulus (riser and drill pipe—two concentric pipes are required) to prevent the onset of hydrate formation. Recovery data of collected oil was readily accessible [10]. However, no data was available concerning the temperature and flowrate of the injected water. A coupled model of fluid flow and heat transfer was developed to estimate the hot water injection temperature and flow rate needed to keep the oil warm enough to avoid hydrate formation. Existing well production data was extensively analyzed to determine the fluid flow and heat transfer of the oil produced through the tubing in the riser. The fluid flow analysis of the production data, coupled with the surrounding seawater pressure and temperature distribution, was used to model the flow and heat transfer of the injected water in the Top Hat recovery system. Two cases were studied in detail—the first assumed a riser made up of uninsulated steel, and the second assumed a steel riser with an outer insulation sheath. The goal was to maintain a water injection temperature high enough to agree with the production data, as well as to maintain a pressure versus temperature distribution outside the hydrate forming region. The flow rate, injection temperature and injection pressure of the hot water are the desired parameters. In order to approximate the operating conditions of the collection system, a coupled model of fluid flow and heat transfer was developed.
- Reservoir Description and Dynamics > Improved and Enhanced Recovery > Waterflooding (1.00)
- Production and Well Operations > Well & Reservoir Surveillance and Monitoring > Production logging (1.00)
- Facilities Design, Construction and Operation > Pipelines, Flowlines and Risers > Risers (1.00)
- Facilities Design, Construction and Operation > Flow Assurance > Hydrates (1.00)
Extension of a Simple Hydrodynamic Slug Flow Model For Transient Hydrate Kinetics
Zerpa, L.E. (Colorado School of Mines) | Rao, I. (Colorado School of Mines) | Aman, Z.M. (Colorado School of Mines) | Sloan, E.D. (Colorado School of Mines) | Koh, C.A. (Colorado School of Mines) | Sum, A.K. (Colorado School of Mines) | Danielson, T. (ConocoPhillips)
ABSTRACT: The formation and accumulation of natural gas hydrates in deep subsea pipelines is 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 flowloop 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 and a pressure drop model to study the effect of hydrate formation on slug flow in gas/water systems. 1. INTRODUCTION Gas hydrates are crystalline inclusion compounds, where water cages trap or enclathrate lighter hydrocarbon species (e.g., methane) typically under high-pressure and lowtemperature conditions (1, 2). Naturally occurring gas hydrates may be found in ocean sediment – typically near thermogenic or biogenic methane sources – and represent a significant potential energy source (3–5). Gas hydrates may also form in conventional energy transport lines (e.g., oil/gas pipelines), representing both a production and safety hazard (1). The present work focuses on enhancing our ability to probe how multiphase flow characteristics for simple systems (gas and water) may change when a hydrate phase is introduced. Our current conceptual picture for hydrate particle formation in water-dominated systems is divided in four steps (Figure 1): gas bubble entrainment in water; hydrate film growth around the interface; particle packing, bedding, or agglomeration; and deposition or plugging (6, 7). The present work is our first attempt to gain greater understanding on how these processes involving hydrates (a third, solid phase) affect the multiphase flow properties of the system (gas and liquid). Current modeling approaches treat the condensed phase (including water and oil) as a homogeneous mixture, with hydrate formation simply augmenting the bulk phase properties (8–11).
Abstract A novel method of delivering thermal energy efficiently for flow assurance and for improved heavy oil production/transport is described. The method, an improved form of magnetic induction heating, uses superparamagnetic nanoparticles that generate heat locally when exposed to a high frequency magnetic field oscillation, via a process known as Neel relaxation. This concept is currently used in biomedicine to locally heat and burn cancerous tissues. Dependence of the rate of heat generation by commercially available, single-domain Fe3O4 nanoparticles of ∼10 nm size, on the magnetic field strength and frequency was quantified. Experiments were conducted for nanoparticles dispersed in water, in hydrocarbon liquid, and embedded in a thin, solid film dubbed "nanopaint". For a stationary fluid heat generation increases linearly with loading of nanoparticles. The rate of heat transfer from the nanopaint to a flowing fluid was up to three times greater than the heat transfer rate to a static fluid. Heating of nanopaint with external magnetic field application has immediate potential impact on oil and gas sector, because such coating could be applied to inner surfaces of pipelines and production facilities. A nanoparticle dispersion could also be injected into the reservoir zone or gravel pack near the production well, so that a thin, adsorbed layer of nanoparticles is created on pore walls. With localized inductive heating of those surfaces, hydrate formation or wax deposition could be prevented; and heavy oil production/transport could be improved by creating a ‘slippage layer’ on rock pore walls and inner surfaces of transport pipes.
- North America > United States (0.46)
- Europe (0.46)
- Energy > Oil & Gas > Upstream (1.00)
- Materials > Chemicals > Commodity Chemicals > Petrochemicals (0.98)
- Reservoir Description and Dynamics (1.00)
- Production and Well Operations > Well & Reservoir Surveillance and Monitoring > Production logging (1.00)
- Facilities Design, Construction and Operation > Flow Assurance (0.86)
- Production and Well Operations > Production Chemistry, Metallurgy and Biology > Inhibition and remediation of hydrates, scale, paraffin / wax and asphaltene (0.68)
Abstract Many aspects of the design and operability of a system to gather and conveyunprocessed hydrocarbons depend on the output from thermo-hydraulic modeling—todefine the physical system, to guide the assessment and reduction of risk, andto establish the operating constraints within which the system can be safelyand reliably operated. Thermo-hydraulic modeling is typically undertaken usingcommercially available and widely used software tools for steady state andtransient modeling. These tools reflect a significant Research and Developmentinvestment by the industry over 20 years. Uncertainties in the accuracy of the results still remain, particularly asparameters are used outside of the range for which validation has beenundertaken. It is also vital to note that the validity of the results alsodepends on the competency and skill of the user to define a range ofappropriate cases, to interpret the results with due regard for the capabilityand limitations of the tools, and to communicate those results to relateddisciplines. Introduction For many aspects of engineering there are well-established industry codes andstandards. Operators may define the requirements for the way their engineeringis to be conducted by reference to these documents. However, there is a lack ofsuch standards in the area of flow assurance, the discipline encompassingmultiphase flow and aspects of production chemistry in the transportation ofunprocessed reservoir fluids. The purpose of this paper is to describe key parts of the requirements in thearea of modeling multiphase flow, and to illustrate, through examples, areaswhere the modeling process may need to be improved. The Value of Reliable Modeling A significant contribution to the success of the oil industry in recent decadeshas been derived from the increased use of multiphase flow transportationsystems, typically to gather production from remote wellhead locations into acentral processing facility. In the case of several currently operatingmulti-field deep-water developments the projects would not have been economicon the basis of having processing facilities over each reservoir, and the useof multiphase gathering systems is therefore a key enabler. The answers which are derived from modeling the multiphase flow through suchsystems therefore matter both at the level of individual design decisions andalso, potentially, at the level of justifying the viability of a majordevelopment. Multiphase flow is complex - typically three ‘phases’ (gas, oil and water)flowing together in the production system which itself will typically includepipelines with changes in orientation (uphill, downhill, and horizontalsections, luted sections at spools, risers), and subject to an overall declinein pressure with length and typically a reduction in temperature with length. The changes in pressure and temperature cause the phase properties (density, viscosity) to change, and the relative quantities of the phases to change asgas expands and liquid evaporates or condenses.
- North America > United States > Texas (0.93)
- North America > Canada > Alberta > Woodlands County (0.24)
Abstract The study of multiphase flow is more difficult and complex in undulatingpipelines due to flow interaction between different pipe sections and influenceof the specific angles being studied. While previous studies (Zheng et al.,1995; Al-Safran et al., 2005) are low angles of hilly pipeline, there is noadequate information on flow characteristics for high angles. The complexity insand transportation in multiphase flow is more aggravated in undulatingpipeline This paper presents experimental investigations to understand the multiphaseflow characteristics, conditions for slug initiation mechanism that wouldenhance sand transport in undulating pipes and assist pipeline design. Theinvestigations were conducted using a 2-inch (ID=50.24 mm) dip facility whichconsists of a downhill pipeline (−24o), a lower elbow (dip) and an uphillpipeline (+24o). The slug initiation mechanisms phenomena were investigated. New flow regimeswere identified for different pipe sections using both visual observation andstatistical parameters. Sand transport characteristics in water and air-waterwere studied at different sand concentration. Also, flow condition to transportsand bed deposit at the dip was determined. Three slug behaviours were observed at the dip: complete stratified flowdownhill with slug initiation at dip; stratified flow (with energetic ripple)downhill with slug initiation and slug growth at the dip; and aerated slugdownhill and slug growth at the dip. This behaviour is different from existingworks on this subject with low angle of inclination. 1. Introduction Solid-liquid-gas flows are commonly encountered in industries such as chemicalprocessing plants, mining of coals and, oil and gas industry. It is apersistent problem in the petroleum industry for many years; most especially inpoorly consolidated reservoir or where hydrocarbon is in the increasing demand. It is quite impossible to produce a sand free hydrocarbon with presence of sandcontrol in place that can prevent sand production with the unprocessedhydrocarbon. However, the alternative approach is to transport sand along withthe multiphase flow hydrocarbon due to factors such as increase in demand ofhydrocarbon and cost to prevent sand production from the reservoir
- Research Report > New Finding (0.83)
- Research Report > Experimental Study (0.51)
- Reservoir Description and Dynamics > Reservoir Fluid Dynamics > Multiphase flow (1.00)
- Production and Well Operations > Well & Reservoir Surveillance and Monitoring > Production logging (1.00)
- Facilities Design, Construction and Operation > Pipelines, Flowlines and Risers > Pipeline transient behavior (0.94)
- Facilities Design, Construction and Operation > Flow Assurance > Solids (scale, sand, etc.) (0.86)
Abstract This manuscript presents a systematic methodology to determine the optimalcritical velocity for sand transport on-the-fly for a given field operatingcondition. Using publicly-available experimental data on sand transport andsand transport models, the methodology combines data clustering andoptimization approaches with statistical analysis. The data clusteringalgorithm is used to select the representative data points that lie closest tothe operating condition, and then, the parameters of the sand transport modelsare fine-tuned using unconstrained optimization with the representative data. Using statistical analysis, the fine-tuned models are compared to identify theones that are most applicable and provide accurate velocity predictions for thegiven operating condition. Upon applying the methodology to a field operatingcondition, the sand transport velocity for the operating condition, assuggested by the methodology, are consistent. Introduction Sand transport models are used to predict the critical velocity, defined as therequired "fluid velocity for particle motion" [1], in order for the fluid to beable to transport the sand particles in the pipe. The transport of the sandparticle must take place in order to prevent the accumulation of sandparticles, which is of importance, as the accumulation of sand particles inpipes can have consequences, such as blockage in the pipeline [2], theprevention of corrosion inhibitors from reaching the bottom of the pipe [3], and erosion due to the decreased flow area in the pipe [4]. In industrialapplications, sand transport models are used to provide a reasonable estimatefor the operating velocity of existing pipelines to ensure that the sandparticles are transported. Due to the wide range of possible operatingconditions that exist, and the different possible mechanisms for particletransport, many sand transport models were developed by different authorsthroughout the years. Fig. 1 shows the critical velocity predictions of 40 sand transport models fora field operating condition, which will be referred as the case study for theremainder of this manuscript. The case study corresponds to solid/liquid flowwith a particle concentration of 5 lbm/1000 bbl, a fluid density of 850 kg/m3,a fluid viscosity of 15 cp, a particle density of 2630 kg/m3, and a particlediameter of 60 µm, for flow in a horizontal pipe with a diameter of 8.25inches. As can be seen from Fig. 1, the values of the predicted sand transportvelocity vary over four orders of magniture. Therefore, out of these 40 models, it is necessary to identify the ones that will provide accurate and consistentvelocity predictions for the given operating condition. This manuscript presents a mechodology, which, on-the-fly, determines the sandtransport models that provide accurate and consistent critical velocitypredictions for an operating condition. In what follows, the details of themethodology are summarized. Then, the methodology is used to determine the sandtransport velocity for the case study, and the results are discussed. Finally, the last section provides concluding remarks and the future directions of thecurrent study. Methodology Our database contains 478 sand transport data for gas/solid flow and 161 sandtransport data for liquid/solid flow, for a total of 639 data points, all ofwhich were obtained from open literature [1, 2, 5-19], where the authors whoconducted the studies were interested in quantifying the sand transportvelocity for different sets of operating conditions. In addition, for thevelocity predictions, 40 sand transport models were considered, and similar tothe sand transport data, the models are also publicly available from theliterature [1-4, 7, 9-11, 18, 20-47], and the models were developed to predictthe velocity required for transporting solids given an operating condition.
- Research Report > New Finding (0.68)
- Research Report > Experimental Study (0.46)
- Reservoir Description and Dynamics (1.00)
- Data Science & Engineering Analytics > Information Management and Systems (1.00)
- Production and Well Operations > Well & Reservoir Surveillance and Monitoring > Production logging (0.66)
- Facilities Design, Construction and Operation > Flow Assurance > Solids (scale, sand, etc.) (0.66)