Using Neural Network Predictive Control for Riser-Slugging Suppression

2009 ◽  
Vol 4 (4) ◽  
Author(s):  
Reza Eslamloueyan ◽  
Elham Hosseinzadeh
Keyword(s):  
Neural Network ◽  
Control System ◽  
Predictive Control ◽  
Oil And Gas ◽  
Neural Model ◽  
Nonlinear Process ◽  
Economic Benefits ◽  
Gas Production ◽  
Ann Model ◽  
Oil And Gas Production

Riser-slugging is a flow regime that can occur in multiphase pipeline-riser systems, and is characterized by severe flow and pressure oscillations. Reducing undesired slugging effects can have great economic benefits. Recently, control methods have been proposed to conquer slugging flow problems in pipeline risers. The advantages of using a control system are that it can be installed on existing oil and gas production facilities with no need for expensive equipment and no significant pressure drop is imposed to the system.In this work, a predictive control system based on Neural Network (NN) model of process is developed for handling and suppressing riser-slugging. An ANN model of the plant is used to predict future response of the nonlinear process. Storkaas dynamic model (Storkaas and Skogestad,2002) is employed for the process simulation. Comparing the results of this research to that of others, indicates that the proposed neural model predictive controller makes a significant improvement in the setpoint tracking especially for higher step change in the setpoint value.

scholarly journals Improving the energy efficiency of oil production using identification and prediction of operating modes of production wells based on data analysis methods, machine learning and neural networks

2019 ◽  
Vol 124 ◽  
pp. 05031 ◽  
Author(s):  
A.M. Sagdatullin
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Control System ◽  
Oil And Gas ◽  
Gas Production ◽  
Operating Conditions ◽  
Identification System ◽  
Oil And Gas Production ◽  
The Neural Network ◽  
And Control

Currently, there is a need to improve the systems and control of pumping equipment in the oil and gas production and oil and gas transport industries. Therefore, an adaptive neural network control system for an electric drive of a production well was developed. The task of expanding the functional capabilities of asynchronous electric motors control of the oil and gas production system using the methods of neural networks is solved. We have developed software modules of the well drive control system based on the neural network, an identification system, and a scheme to adapt the control processes to changing load parameters, that is, to dynamic load, to implement the entire system for real-time control of the highspeed process. In this paper, based on a model of an identification block that includes a multilayered neural network of direct propagation, the control of the well system was implemented. The neural network of the proposed system was trained on the basis of the error back-propagation algorithm, and the identification unit works as a forecaster of system operation modes based on the error prediction. In the initial stage of the model adaptation, some fluctuations of the torque are observed at the output of the neural network, which is associated with new operating conditions and underestimated level of learning. However, the identification object and control system is able to maintain an error at minimum values and adapt the control system to a new conditions, which confirms the reliability of the proposed scheme.

scholarly journals Aspects of sustainable development of industry in Kazakhstan

2019 ◽  
Vol 135 ◽  
pp. 04043
Author(s):  
Svetlana Faizullina ◽  
Ainur Isaeva ◽  
Lailya Matkarimova ◽  
Aigul Zhuzbaeva
Keyword(s):  
Sustainable Development ◽  
Oil And Gas ◽  
Economic Benefits ◽  
Gas Production ◽  
Health Impacts ◽  
Energy Market ◽  
Global Energy ◽  
Oil And Gas Production ◽  
World Energy ◽  
The World

This article discusses the economic benefits of uranium mining, as well as its environmental and health impacts. Sustainable development includes several aspects: energy, water, the environment, food and the economy, and ensuring each of these aspects is a serious problem. Energy is at the center of other aspects of sustainability, as it has a direct relationship with water, food, and the environment. Uranium is Kazakhstan’s top priority in the global energy market. In the world, there are different opinions on the development of uranium production, increasing the value of atomic energy. Apparently, this should be preceded by a crisis in the field of oil and gas production in recent years, in connection with which the world energy market should have a diversified course depending on various energy sources. Kazakhstan is a country rich in uranium. In addition, over the years of independence, we have increased production almost four times and maintain leadership in the world. Therefore, uranium production is the most important advantage of our global energy space today.

Study of Slug Control Techniques in Pipeline Systems

2014 ◽  
Author(s):  
P. C. C. Monteiro ◽  
L. Loureiro Silva ◽  
J. L. A. Vidal ◽  
Theodoro A. Netto
Keyword(s):  
Control System ◽  
Flow Rate ◽  
Oil And Gas ◽  
Gas Production ◽  
Low Flow ◽  
Flow Loop ◽  
Two Phase ◽  
Automated Control ◽  
Oil And Gas Production ◽  
Automated Control System

Severe slugging may occur at low flow rate conditions when a downward inclined pipeline is followed by a vertical riser. This phenomenon is undesirable for offshore oil and gas production due to large pressure and flow rate fluctuations. It is of great technological relevance to develop reliable and economical means of severe slugging mitigation. This study aims to develop an automated control system to detect and mitigate the formation of severe slugging through a choke valve and a series of sensors. As a first step, an overall flow map is generated to indicate the region within which severe slugging may occur based on Boe’s criterion [1] and Taitel’s model [2, 3]. It was possible to obtain different flow patterns by controlling the rate of water and gas injection. The aim of this paper is, however, the formation of severe slugs and study of mitigation techniques. In the control part, we used a choke valve controlled by software which is in feedback with data from a system with pressure, temperature, flow, which are able to measure even small changes in the relevant parameters to the model. A two-phase flow loop was built for the study of severe slugging in pipeline-riser system with air and water as work fluids. The inner diameter of riser and flowline is 76.2 mm. The riser is 20 meters high and the flowline is 15 meters long and could be inclined upward or downward up to 8-degree. It has been shown by experiments how riser slugging can be controlled by automated control system.

scholarly journals A Novel Multi-Input AlexNet Prediction Model for Oil and Gas Production

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Yang Wang ◽  
Yin Lv ◽  
Dali Guo ◽  
Shu Zhang ◽  
Shixiang Jiao
Keyword(s):  
Neural Network ◽  
Prediction Model ◽  
Oil And Gas ◽  
Nearest Neighbor ◽  
Gas Production ◽  
Support Vector ◽  
K Nearest Neighbor ◽  
Oil And Gas Production ◽  
Network Support ◽  
Parameter Values

In the process of oilfield development, it is important to predict the oil and gas production. The predicted value of oil production is the amount of oil that may be obtained within a certain area over a certain period. Because of the current demand for oil and gas production prediction, a prediction model using a multi-input convolutional neural network based on AlexNet is proposed in this paper. The model predicts real oilfield data and achieves good results: increasing prediction accuracy by 17.5%, 20.8%, 11.6%, 8.9%, 6.9%, and 14.9% with respect to the backpropagation neural network, support vector machine, artificial neural network, radial basis function neural network, K-nearest neighbor, and decision tree methods, respectively. It addresses the uncertainty of oil and gas production caused by the change in parameter values during the process of petroleum exploitation and has far-reaching application significance.

ESTIMATED NET ECONOMIC BENEFITS FROM AUSTRALIA'S UPSTREAM OIL AND GAS INDUSTRY: 1980-2010

1996 ◽  
Vol 36 (2) ◽  
pp. 130
Author(s):  
L. Hogan ◽  
S. Thorpe ◽  
S. Zheng ◽  
L. Ho Trieu ◽  
G. Fok ◽  
...  
Keyword(s):  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Economic Benefits ◽  
Gas Production ◽  
Export Market ◽  
Gas Industry ◽  
Oil And Gas Production ◽  
The Past ◽  
Australian Economy ◽  
Oil And Gas Resources

Australia's oil and gas resources industry has made a significant contribution to the Australian economy and is expected to continue to do so over the next 15 years and beyond. While oil and gas production from Bass Strait has been the most important part of the industry in the past, offshore oil and gas production has increased strongly in northwest Australia over the past decade. Future growth in the industry is expected to be mainly associated with further strong growth in gas production for both domestic use and the export market. This paper contains an assessment of some major net economic benefits from the exploration, development and production of Australia's oil and gas resources during the period 1980 to 2010.

A Case History: Evaluating Well Completions in the Eagle Ford Shale Using a Data-Driven Approach

2015 ◽  
Author(s):  
Amir M. Nejad ◽  
Stanislav Sheludko ◽  
Robert F. Shelley ◽  
Trey Hodgson ◽  
Riley McFall
Keyword(s):  
Neural Network ◽  
Neural Network Model ◽  
Oil And Gas ◽  
Gas Production ◽  
Data Driven ◽  
Eagle Ford Shale ◽  
Eagle Ford ◽  
Oil And Gas Production ◽  
Treatment Designs ◽  
Different Parts

Abstract Unconventional shale resources are key hydrocarbon sources, gaining importance and popularity as hydrocarbon reservoirs both in the United States and internationally. Horizontal wellbores and multiple transverse hydraulic fracturing are instrumental factors for economical production from shale assets. Hydraulic fracturing typically represents a major component of total well completion costs, and many efforts have been made to study and investigate different strategies to improve well production and reduce costs. The focus of this paper is completion effectiveness evaluation in different parts of the Eagle Ford Shale Formation, and our objective is to identify appropriate completion strategies in the field. A data-driven neural network model is trained on the database comprised of multiple operators' well data. In this model, drilling and mud data are used as indicators for geology and reservoir-related parameters such as pressure, fluid saturation and permeability. Additionally, completion- and fracture-related parameters are also used as model inputs. Because wells are pressure managed differently, normalized oil and gas production is used as a model output. Thousands of neural networks are trained using genetic algorithm in order to fully evaluate hidden correlations within the database. This results in selection of a neural network that is able to understand reservoir, completion and frac differences between wells and identify how to improve future completion/stimulation designs. The final neural network model is successfully developed and tested on two separate data sets located in different parts of the Eagle Ford Shale oil window. Further, an additional test data set comprised of eight wells from a third field location is used to validate the predictive usefulness of the data-driven model. Under-producing wells were also identified by the model and new fracture designs were recommended to improve well productivity. This paper will be useful for understanding the effects of completion and fracture treatment designs on well productivity in the Eagle Ford. This information will help operators select more effective treatment designs, which can reduce operational costs associated with completion/fracturing and can improve oil and gas production.

scholarly journals Construction and application of reservoir development measure benefit evaluation system

2021 ◽  
Vol 236 ◽  
pp. 01023
Author(s):  
Dan Han ◽  
Debin Zhang
Keyword(s):  
Oil Recovery ◽  
Evaluation System ◽  
Oil And Gas ◽  
Effective Rate ◽  
Economic Benefits ◽  
Gas Production ◽  
Oil Well ◽  
Oil And Gas Production ◽  
Benefit Evaluation ◽  
Low Efficiency

The reservoir passes the peak of reserves.The reserves of new investment and development are decreasing year by year. The reserve resources are insufficient. Some of the main development units have entered the stage of secondary or tertiary oil recovery. The dependence of stable oil and gas production on measure production increases continuously. Under this background, the workload of oil well measures increases year by year. It is difficult to control the operation cost of measures. As a result, the overall economic benefits of oilfield enterprises have been declining year by year.The cost of ineffective measures has become an important factor restricting the economic development of oilfields. Through the construction of measures benefit evaluation system.Strengthen the controllability and predictability of each stage of implementation. Special attention should be paid to the pre control management of high cost wells and the transformation of production mode of low efficiency wells. Strictly follow the "ex ante argument, adjustment in matters, and post evaluation optimization" measures to run the management mode. Realize the reasonable allocation of workload and cost, and improve the effective rate of return of funds.

Sign in / Sign up

Export Citation Format

Share Document