Flow Assurance

The oil and gas business is serious business and involves millions of dollars so whatever mitigates flow assurance is taken seriously. One of such things is natural gas hydrates. Hydrates are crystalline solids formed when water under low temperatures and high pressures encapsulated natural gases (C1–C4). They form blockages and impede the flow of gas which can lead to the loss of millions of dollars and at times lead to personnel death. Mitigation of gas hydrates has always been with chemicals especially for areas like deep offshore where accessibility is difficult. The chemicals that are in use currently are generally synthetic, expensive and hazardous to lives and environment hence the need for readily available locally sourced materials that are eco-friendly. This study considers and screens a locally sourced surfactant from the plant family caricaceae’ Extract (CE) as a gas hydrate inhibitor in a locally fabricated 39.4-inch mini flow loop of ½ inch internal diameter (ID) which...

It is almost impossible to solve the modern fluid flow problems without the use of Computational Fluid Dynamics (CFD). In petroleum industry, flow simulations assist engineers to develop the most efficient well design and it is essential to understand the multiphase flow details. However, despite the high accuracy, performing the numerical simulation fall short in providing the required results in timely manner. This article presents two case studies of Smart Proxy Models (SPM) utilizing artificial intelligence (AI) and Machine Learning (ML) techniques to appraise the behavior of the chaotic system and predict the dynamic features including pressure, velocity and the evolution of phase fraction within the process at each time-step at a much lower run time. Proposed cases concentrate on 2-D dam-break and 3-D fluidized bed problems, using OpenFOAM and MFiX, CFD software applications, respectively. This paper focuses on building and improving the artificial neural network (ANN) models ...

Pressure - Volume - Temperature (PVT) analyses simulate the reservoir fluid behavior while flowing from the reservoir to the surface under varying pressure, volume and temperature conditions. There are several PVT simulators that perform PVT calculations. Accurate characterization of a fluid is very important for further studies and reservoir simulations in all reservoir engineering aspects. Because there are a few equations of state and many types of reservoir and reservoir fluids, experimental data does not perfectly match with the PVT simulation results. Low API black oils include heavy hydrocarbons. Therefore, regression and characterization of plus fractions are needed in order to get better results from the PVT simulators. PVT data is usually used for field development program, reserve calculations, and EOR/IOR implementations such as gas flooding. In this study, PVT experiments, which are Constant Composition Experiment, 0 - Flash Experiment, Gas and Oil Compositional Analysi...

One of the most relevant flow assurance issues in oil transportation is indeed the phenomena of wax deposition. Wax deposition occurs when the temperature along the pipeline falls below a point where it is described as Wax Appearance Temperature (WAT) The deposition may cause a lot of problems to the industry and definitely will involve expensive cause to overcome the problem. The flow system was built for Rawat field which is consists of (13) wells in the Rawat/Wateesh field. In this studies a series of cases were carried out at different flow rates, ambient temperature to study falling temperature through f pipline using PIPESIM Software and providing data from central petroleum laboratory and Rawat operating company. To check that temperature at all points along the flow line and trunk line is above the pour point and wax appearance temperature, check the requirement of heater, heat tracing and insulation for the pipelines more ever is used to studies the influence of changing fl...

The article provides information on temperature and pressure regimes in submarine gas pipelines, their study, as well as a brief analysis of the difficulties encountered during transportation and various methods for their prevention. The introduction section provides general information on gas-condensate fields, their characteristics and difficulties in operation, as well as temperature and pressure regimes during the transportation of the product from the DSF in the pipeline. As objective of the problem is the complexity of the product composition and the formation of a new mixture by mixing products from different fields during transportation, also the difficulties created by this mixture during transportation are noted. Keywords: “DSF”– Deep Sea Foundations, hydrate, crystallization centers, turbulence, corrosion.

The rheological behaviour of crude oil mixtures comprising both heavy and light components along with chemical additives is of significant interest due to its relevance in the petroleum industry. Understanding the flow properties of these mixtures is crucial for efficient transportation, processing, and refining operations. This study investigates the effectiveness of incorporating light crude oil and nanoparticles as additives to mitigate wax-related flow issues. The test involves six different waxy/heavy and light crude oil mixture concentrations along with Graphene Oxide and Silicon Dioxide nanoparticles. Rheological tests were conducted to evaluate the impact of these additives on the flow behaviour of waxy crude oil. The rheological characterization involved measuring the viscosity, yield stress, and shear rate dependencies of waxy crude oil samples with varying concentrations of light crude oil and nanoparticles. Nano-materials have emerged as promising candidates for mitigating wax deposition issues and enhancing the fluidity of crude oil. Nevertheless, the intricate nature of crude oil has made it challenging to elucidate the underlying mechanisms governing wax resolution, crystal modification, and flow improvement. The results revealed notable improvements in the rheological properties of the treated crude oil, including reduced viscosity and enhanced flowability, even at low temperatures. The incorporation of light crude oil and nanoparticles proved to be a promising strategy for modifying the rheological behaviour of waxy crude oil, ensuring improved flow assurance. This study contributes to understanding innovative approaches to address flow challenges in waxy crude oil systems, thereby offering potential solutions for the oil and gas industry.

Organic deposition predominantly in the near well bore and in production tubing can create serious oilfield problems such as flow restrictions, near wellbore damage, efficiency of crude processing units and etc. As the reservoir depleted over the time, the solid deposition can lead to a steep decline in productivity of wells. The deposition of organic solids is one of many flow assurance problems faced by operators in Malaysia. It has been observed that, after years of production, many fields in Malaysia are suffering from organic solid deposition problem. This phenomenon is predominantly caused by changes in temperature, pressure and composition/morphology of the crude oil over time. To perform organic deposit removal treatment and prevention in the well, the nature of the solid should be characterized. If the deposit sample is organic mainly, it is important to quantify the various organic fractions of the solid sample collected from the production facilities. This paper explains ...

The optimization of artificial gas lift techniques plays a crucial role in the advancement of oil field development. This study focuses on investigating the impact of gas lift design and optimization on production outcomes within the Mishrif formation of the Halfaya oil field. A comprehensive production network nodal analysis model was formulated using a PIPESIM Optimizer-based Genetic Algorithm and meticulously calibrated utilizing field-collected data from a network comprising seven wells. This well group encompasses three directional wells currently employing gas lift and four naturally producing vertical wells. To augment productivity and optimize network performance, a novel gas lift design strategy was proposed. The optimization of gas allocation was executed to maximize oil production rates while minimizing the injected gas volume, thus achieving optimal oil production levels at the most effective gas injection volume for the designated network. The utilization of the PIPESIM...

Gas hydrate formation in production and transmission pipelines and consequent plugging of these lines have been a major flow-assurance concern of the oil and gas industry for the last 75 years. Gas hydrate formation rate is one of the most important topics related to the kinetics of the process of gas hydrate crystallization. The main purpose of this study is investigating phenomenon of gas hydrate formation with the Presence of kinetic Inhibitors in operation gas transmission, and prediction of gas hydrate formation rate in the pipeline. In this regard, by using experimental data and Intelligent Systems (Artificial neural networks and adaptive neural-fuzzy system), two different high efficient and accurate models were designed to predict hydrate formation rate of CO2, C1, C3, and i-C4. It was found that such models can be used as powerful tools, for prediction of gas hydrate formation rate with total average of absolute deviation less than 6%.

The production of oil and natural gas contributes to a significant amount of revenue generation in Malaysia thereby strengthening the country’s economy. The flow assurance industry is faced with impediments during smooth operation of the transmission pipeline in which gas hydrate formation is the most important. It affects the normal operation of the pipeline by plugging it. Under high pressure and low temperature conditions, gas hydrate is a crystalline structure consisting of a network of hydrogen bonds between host molecules of water and guest molecules of the incoming gases. Industry uses different types of chemical inhibitors in pipeline to suppress hydrate formation. To overcome this problem, machine learning algorithm has been introduced as part of risk management strategies. The objective of this paper is to utilize Machine Learning (ML) model which is Gaussian Process Regression (GPR). GPR is a new approach being applied to mitigate the growth of gas hydrate. The input para...

It is almost impossible to solve the modern fluid flow problems without the use of Computational Fluid Dynamics (CFD). In petroleum industry, flow simulations assist engineers to develop the most efficient well design and it is essential to understand the multiphase flow details. However, despite the high accuracy, performing the numerical simulation fall short in providing the required results in timely manner. This article presents two case studies of Smart Proxy Models (SPM) utilizing artificial intelligence (AI) and Machine Learning (ML) techniques to appraise the behavior of the chaotic system and predict the dynamic features including pressure, velocity and the evolution of phase fraction within the process at each time-step at a much lower run time. Proposed cases concentrate on 2-D dam-break and 3-D fluidized bed problems, using OpenFOAM and MFiX, CFD software applications, respectively. This paper focuses on building and improving the artificial neural network (ANN) models ...