A committee machine based soft sensor as an alternative to multiphase flow meter for oil flow rate prediction of the wells

2014 ◽  
Vol 26 (6) ◽  
pp. 2719-2729 ◽  
Author(s):  
Shahram Mollaiy-Berneti
Keyword(s):  
Multiphase Flow ◽  
Flow Rate ◽  
Soft Sensor ◽  
Flow Meter ◽  
Committee Machine ◽  
Rate Prediction ◽  
Oil Flow

scholarly journals Using data analytics to quantify the impact of production test uncertainty on oil flow rate forecast

2020 ◽  
Vol 75 ◽  
pp. 7 ◽  
Author(s):  
Danielle D. Monteiro ◽  
Maria Machado Duque ◽  
Gabriela S. Chaves ◽  
Virgílio M. Ferreira Filho ◽  
Juliana S. Baioco
Keyword(s):  
Multiphase Flow ◽  
Flow Rate ◽  
Data Analytics ◽  
Flow Analysis ◽  
Flow Simulation ◽  
Production Test ◽  
Total Production ◽  
Oil Flow ◽  
Using Data ◽  
The Impact

In general, flow measurement systems in production units only report the daily total production rates. As there is no precise control of individual production of each well, the current well flow rates and their parameters are determined when production tests are conducted. Because production tests are performed periodically (e.g., once a month), information about the wells is limited and operational decisions are made using data that are not updated. Meanwhile, well properties and parameters from the production test are typically used in multiphase flow models to forecast the expected production. However, this is done deterministically without considering the different sources of uncertainties in the production tests. This study aims to introduce uncertainties in oil flow rate forecast. To do this, it is necessary to identify and quantify uncertainties from the data obtained in the production tests, consider them in production modeling, and propagate them by using multiphase flow simulation. This study comprises two main areas: data analytics and multiphase flow simulation. In data analytics, an algorithm is developed using R to analyze and treat the data from production tests. The most significant stochastic variables are identified and data deviation is adjusted to probability distributions with their respective parameters. Random values of the selected variables are then generated using Monte Carlo and Latin Hypercube Sampling (LHS) methods. In multiphase flow simulation, these possible values are used as input. By nodal analysis, the simulator output is a set of oil flow rate values, with their interval of occurrence probabilities. The methodology is applied, using a representative Brazilian offshore field as a case study. The results show the significance of the inclusion of uncertainties to achieve greater accuracy in the multiphase flow analysis of oil production.

Evaluation of a Close Coupled Slotted Orifice, Electric Impedance, and Swirl Flow Meters for Multiphase Flow

2013 ◽  
Author(s):  
Gerald Morrison ◽  
Sahand Pirouzpanah ◽  
Muhammet Cevik ◽  
Abhay Patil
Keyword(s):  
Multiphase Flow ◽  
Flow Rate ◽  
Swirl Flow ◽  
Response Curves ◽  
Flow Meter ◽  
Two Phase ◽  
Flow Meters ◽  
Mixture Density ◽  
Wide Range ◽  
Impedance Sensor

The feasibility of a multiphase flow meter utilizing closely coupled slotted orifice and swirl flow meters along with an impedance sensor is investigated. The slotted flow meter has been shown to exhibit well behaved response curves to two phase flow mixtures with the pressure difference monotonically increasing with mixture density and flow rate. It has been determined to have less than 1% uncertainty in determining the flow rate if the density of the fluid is known. Flow visualizations have shown that the slotted orifice is a very good mixing device as well producing a homogenous mixture for several pipe diameters downstream of the plate. This characteristic is utilized to provide a homogeneous mixture at the inlet to the swirl meter. This is possible since the slotted orifice is relatively insensitive to upstream and downstream flow disturbances. The swirl meter has been shown to indicate decreased flow rate as the mixture density increases which is opposite to the slotted orifice making the solution of the two meter outputs to obtain density and flow rate feasible. Additional instrumentation is included. Between the slotted orifice and swirl meter where the flow is homogenous a custom manufactured electrical impedance sensor is installed and monitored. This array of instrumentation will provide three independent measurements which are evaluated to determine which system of equations are robust enough to provide accurate density and flow rate measurement over a wide range of gas volume fractions using a very compact system.

scholarly journals Prediction of oil flow rate through an orifice flow meter: Artificial intelligence alternatives compared

Petroleum ◽  
2018 ◽  
Author(s):  
Hamzeh Ghorbani ◽  
David A. Wood ◽  
Abouzar Choubineh ◽  
Afshin Tatar ◽  
Pejman Ghazaeipour Abarghoyi ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Flow Rate ◽  
Flow Meter ◽  
Oil Flow ◽  
Orifice Flow ◽  
Orifice Flow Meter

Simulation and flow rate prediction method for steam flow meter using circumferential heater

2020 ◽  
Vol 2020 (0) ◽  
pp. J05305
Author(s):  
Masaya OKAMURA ◽  
Kazushi MIYATA ◽  
Yoshinori HAMAMOTO ◽  
Shuichi UMEZAWA ◽  
Shuichi OMORI
Keyword(s):  
Flow Rate ◽  
Prediction Method ◽  
Steam Flow ◽  
Flow Meter ◽  
Rate Prediction

Application of Machine Learning Algorithms and Integrated Production Modelling to Improve Accuracy of Liquid Production Rate Measurements Using Multiphase Flow Meters

2021 ◽  
Author(s):  
Maksim Yuryevich Nazarenko ◽  
Anatoly Borisovich Zolotukhin
Keyword(s):  
Machine Learning ◽  
Multiphase Flow ◽  
Production Rate ◽  
Flow Rate ◽  
Learning Algorithms ◽  
Oil Production ◽  
Machine Learning Algorithms ◽  
Flow Meter ◽  
Integrated Production ◽  
Production Modelling

Abstract Objectives/Scope: During the period of two years the difference between sum of daily oil flow rate measurements of each oil production well using multiphase flow meter (MPFM) and cumulative daily oil production rate measured by custody transfer meter increased overall by 5%. For some wells inaccuracy of MPFM liquid rate measurement could reach 30-50%. The main goal of this research was to improve the accuracy of multiphase flow meter production rate measurements. Methods, Procedures, Process: More than 80 oil production wells were involved in the research, more than 100 flow rate tests were carried out. Machine learning methods such as supervised learning algorithms (linear and nonlinear regressions, method of gradient descent, finite differences algorithm, etc.) have been applied coupled with Integrated production modelling tools such as PROSPER and OpenServer in order to develop a function representing correlation between MPFM parameters and flow rate error. Results, Observations, Conclusions: The difference between cumulative daily oil production rate measured by custody transfer meter and multiphase flow meters decreased to 0.5%. The solution has been officially applied at the oil field and saved USD 500K to the Company. The reliability of the function was then proved by the vendor of MPFMs. Novel/Additive Information: For the first time machine learning algorithms coupled with Integrated Production modelling tools have been used to improve the accuracy of multiphase flow meter production rate measurements.

scholarly journals Study of Injection Method for Maximizing Oil-Cooling Performance of Electric Vehicle Motor with Hairpin Winding

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 747
Author(s):  
Taewook Ha ◽  
Dong Kyu Kim
Keyword(s):  
Electric Vehicle ◽  
Flow Rate ◽  
Film Formation ◽  
Formation Rate ◽  
Cooling Performance ◽  
Oil Film ◽  
Injection Method ◽  
Cooling Method ◽  
Oil Flow ◽  
Oil Injection

The oil injection method was studied to maximize the cooling performance of an electric vehicle motor with a hairpin winding. The cooling performance of the motor using the oil cooling method is proportional to the contact area of the oil and the coil. A numerical analysis was conducted to examine the effect of the spray nozzle type on the oil flow. The dripping nozzle forms the thickest oil film on the coil, making it the most effective for cooling of hairpin-type motors. Subsequently, an experimental study was conducted to optimize the nozzle diameter and number of nozzles. When the inlet diameter and number was 6.35 mm and 6, the oil film formation rate was 53%, yielding the most uniform oil film. Next, an experiment was performed to investigate the effects of the oil temperature and flow rate on the oil flow. The oil film formation rate was the highest (83%) when the oil temperature was 40 °C and the flow rate was 6 LPM.

scholarly journals Role of Shearing Dispersion and Stripping in Wax Deposition in Crude Oil Pipelines

Energies ◽  
2019 ◽  
Vol 12 (22) ◽  
pp. 4325
Author(s):  
Zhihua Wang ◽  
Yunfei Xu ◽  
Yi Zhao ◽  
Zhimin Li ◽  
Yang Liu ◽  
...  
Keyword(s):  
Crude Oil ◽  
Flow Rate ◽  
Critical Flow ◽  
Wax Deposition ◽  
Dominant Effect ◽  
Critical Flow Rate ◽  
Oil Pipelines ◽  
Oil Flow ◽  
Shearing Mechanism

Wax deposition during crude oil transmission can cause a series of negative effects and lead to problems associated with pipeline safety. A considerable number of previous works have investigated the wax deposition mechanism, inhibition technology, and remediation methods. However, studies on the shearing mechanism of wax deposition have focused largely on the characterization of this phenomena. The role of the shearing mechanism on wax deposition has not been completely clarified. This mechanism can be divided into the shearing dispersion effect caused by radial migration of wax particles and the shearing stripping effect caused by hydrodynamic scouring. From the perspective of energy analysis, a novel wax deposition model was proposed that considered the flow parameters of waxy crude oil in pipelines instead of its rheological parameters. Considering the two effects of shearing dispersion and shearing stripping coexist, with either one of them being the dominant mechanism, a shearing dispersion flux model and a shearing stripping model were established. Furthermore, a quantitative method to distinguish between the roles of shearing dispersion and shearing stripping in wax deposition was developed. The results indicated that the shearing mechanism can contribute an average of approximately 10% and a maximum of nearly 30% to the wax deposition process. With an increase in the oil flow rate, the effect of the shearing mechanism on wax deposition is enhanced, and its contribution was demonstrated to be negative; shear stripping was observed to be the dominant mechanism. A critical flow rate was observed when the dominant effect changes. When the oil flow rate is lower than the critical flow rate, the shearing dispersion effect is the dominant effect; its contribution rate increases with an increase in the oil flow temperature. When the oil flow rate is higher than the critical flow rate, the shearing stripping effect is the dominant effect; its contribution rate increases with an increase in the oil flow temperature. This understanding can be used to design operational parameters of the actual crude oil pipelines and address the potential flow assurance problems. The results of this study are of great significance for understanding the wax deposition theory of crude oil and accelerating the development of petroleum industry pipelines.

Sign in / Sign up

Export Citation Format

Share Document