Numerical Simulation of Gas Lift Optimization Using Artificial Intelligence for a Middle Eastern Oil Field

Mohammed Ahmed Al-Janabi; Omar F. Al-Fatlawi; Dhifaf Jaafar Sadeq; Haider Abdulmuhsin Mahmood; Mustafa Alaulddin Al-Juboori

doi:10.2118/207341-ms

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Publication Date

Tue Nov 09 2021

Journal Name

Abu Dhabi International Petroleum Exhibition & Conference

DOI

10.2118/207341-ms

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Numerical Simulation of Gas Lift Optimization Using Artificial Intelligence for a Middle Eastern Oil Field

evolutionary algorithm

gas lift

artificial intelligence

upstream oil & gas

machine learning

optimization problem

correlation

presented

allocation

reservoir pressure

Mohammed Ahmed Al-Janabi

Omar F. Al-Fatlawi

Dhifaf Jaafar Sadeq

Haider Abdulmuhsin Mahmood

Mustafa Alaulddin Al-Juboori

...Show More Authors

AbstractArtificial lift techniques are a highly effective solution to aid the deterioration of the production especially for mature oil fields, gas lift is one of the oldest and most applied artificial lift methods especially for large oil fields, the gas that is required for injection is quite scarce and expensive resource, optimally allocating the injection rate in each well is a high importance task and not easily applicable. Conventional methods faced some major problems in solving this problem in a network with large number of wells, multi-constrains, multi-objectives, and limited amount of gas. This paper focuses on utilizing the Genetic Algorithm (GA) as a gas lift optimization algorithm to tackle the challenging task of optimally allocating the gas lift injection rate through numerical modeling and simulation studies to maximize the oil production of a Middle Eastern oil field with 20 production wells with limited amount of gas to be injected. The key objective of this study is to assess the performance of the wells of the field after applying gas lift as an artificial lift method and applying the genetic algorithm as an optimization algorithm while comparing the results of the network to the case of artificially lifted wells by utilizing ESP pumps to the network and to have a more accurate view on the practicability of applying the gas lift optimization technique. The comparison is based on different measures and sensitivity studies, reservoir pressure, and water cut sensitivity analysis are applied to allow the assessment of the performance of the wells in the network throughout the life of the field. To have a full and insight view an economic study and comparison was applied in this study to estimate the benefits of applying the gas lift method and the GA optimization technique while comparing the results to the case of the ESP pumps and the case of naturally flowing wells. The gas lift technique proved to have the ability to enhance the production of the oil field and the optimization process showed quite an enhancement in the task of maximizing the oil production rate while using the same amount of gas to be injected in the each well, the sensitivity analysis showed that the gas lift method is comparable to the other artificial lift method and it have an upper hand in handling the reservoir pressure reduction, and economically CAPEX of the gas lift were calculated to be able to assess the time to reach a profitable income by comparing the results of OPEX of gas lift the technique showed a profitable income higher than the cases of naturally flowing wells and the ESP pumps lifted wells. Additionally, the paper illustrated the genetic algorithm (GA) optimization model in a way that allowed it to be followed as a guide for the task of optimizing the gas injection rate for a network with a large number of wells and limited amount of gas to be injected.

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Publication Date

Mon Aug 10 2020

Journal Name

Journal Of Petroleum Exploration And Production Technology

Geomechanical modelling and two-way coupling simulation for carbonate gas reservoir

Barzan I.

M S

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AbstractGeomechanical modelling and simulation are introduced to accurately determine the combined effects of hydrocarbon production and changes in rock properties due to geomechanical effects. The reservoir geomechanical model is concerned with stress-related issues and rock failure in compression, shear, and tension induced by reservoir pore pressure changes due to reservoir depletion. In this paper, a rock mechanical model is constructed in geomechanical mode, and reservoir geomechanics simulations are run for a carbonate gas reservoir. The study begins with assessment of the data, construction of 1D rock mechanical models along the well trajectory, the generation of a 3D mechanical earth model, and runni ... Show More

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Publication Date

Sun Mar 29 2020

Journal Name

Iraqi Journal Of Chemical And Petroleum Engineering

Water Injection for Oil Recovery in Mishrif Formation for Amarah Oil Field

History matching

Amarah

Water injection

Mishrif

Ayat Ahmed

Abdul Aali

Aqeel S.

...Show More Authors

The water injection of the most important technologies to increase oil production from petroleum reservoirs. In this research, we developed a model for oil tank using the software RUBIS for reservoir simulation. This model was used to make comparison in the production of oil and the reservoir pressure for two case studies where the water was not injected in the first case study but adding new vertical wells while, later, it was injected in the second case study. It represents the results of this work that if the water is not injected, the reservoir model that has been upgraded can produce only 2.9% of the original oil in the tank. This case study also represents a drop in reservoir pressure, which was not enough to support oil production

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(5)

Publication Date

Sun Dec 01 2019

Journal Name

Computers And Electronics In Agriculture

Meteorological data mining and hybrid data-intelligence models for reference evaporation simulation: A case study in Iraq

Khabat

Prasad

Mohammad Taghi

Salih

Mazen Ismaeel

Mehdi

Binh Thai

Fatemeh

Chongchong

Zaher Mundher

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(112)

Publication Date

Sun Dec 10 2023

Journal Name

Journal Of Applied Engineering And Technological Science (jaets)

The Role of Artificial Intelligence in Diagnosing Heart Disease in Humans: A Review

Electrocardiogram

Waves

Heartbeats

Diagnosing

Medical

Signal

Tamara Hameed Yousif

Mohammed

...Show More Authors

The electrical activity of the heart and the electrocardiogram (ECG) signal are fundamentally related. In the study that has been published, the ECG signal has been examined and used for a number of applications. The monitoring of heart rate and the analysis of heart rhythm patterns, the detection and diagnosis of cardiac diseases, the identification of emotional states, and the use of biometric identification methods are a few examples of applications in the field. Several various phases may be involved in the analysis of electrocardiogram (ECG) data, depending on the type of study being done. Preprocessing, feature extraction, feature selection, feature modification, and classification are frequently included in these stages. Ever

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(3)

Publication Date

Sun Jan 01 2023

Journal Name

International Journal Of Intelligent Systems And Applications In Engineering

Artificial Intelligence Based Statistical Process Control for Monitoring and Quality Control of Water Resources: A Complete Digital Solution

Meervat Razzaq

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(5)

Publication Date

Tue Jun 18 2024

Journal Name

2023 Asee Annual Conference & Exposition Proceedings

Study of Artificial Intelligence Computing Devices for Undergraduate Computer Science and Engineering Labs

Bahaa

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Publication Date

Mon Jan 01 2024

Journal Name

Open Engineering

Using ANN for well type identifying and increasing production from Sa’di formation of Halfaya oil field – Iraq

tight formation

increasing oil production

reservoir management

well production types

ANN applications

Ghanim M.

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AbstractThe current study focuses on utilizing artificial intelligence (AI) techniques to identify the optimal locations of production wells and types for achieving the production company’s primary objective, which is to increase oil production from the Sa’di carbonate reservoir of the Halfaya oil field in southeast Iraq, with the determination of the optimal scenario of various designs for production wells, which include vertical, horizontal, multi-horizontal, and fishbone lateral wells, for all reservoir production layers. Artificial neural network tool was used to identify the optimal locations for obtaining the highest production from the reservoir layers and the optimal well type. Fo ... Show More

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(1)

Publication Date

Thu Jun 29 2023

Journal Name

Iraqi Journal Of Chemical And Petroleum Engineering

The Effect of Variable Parameters on Carbon Residue of Iraqi Vacuum Gas Oil using Ultrasound Techniques

vacuum gas oil processing

ultrasonic cavitation

heavy oil

oil upgrading

petroleum

power amplitude

Fatima H.

Tariq M.

Hind

...Show More Authors

An ultrasonic treatment was applied to the vacuum gas oil at intervals of 5 to 30 minutes, at 70°C. In this work, the improvement of the important properties of Iraqi vacuum gas oil, such as carbon residue, was studied with several parameter conditions that affect vacuum efficiency, such as sonication time (5, 10, 15, 20, 25, and 30) min, power amplitude (10–50%). After ultrasonic treatment, the carbon residue of vacuum gas oil was evaluated using a Conradson carbon residue meter (ASTM D189). The experiment revealed that the oil's carbon residue had decreased by 16%. As a consequence of the experiment It was discovered that ultrasonic treatment might reduce the carbon residual and density of oil samples being studied. It also notice

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(1)

Publication Date

Fri Aug 16 2024

Journal Name

International Journal Of Mathematics And Computer Science

Artificial Intelligence Techniques to Identify Individuals through Palm Image Recognition

Palm print

Random Forest

Support Vector Machine

k-NN

SqueezNet

Machine Learning

Wisal Hashim

Shahlaa

Samera Shams

Aseel

...Show More Authors

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

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(6)

(3)

Publication Date

Mon Apr 24 2017

Journal Name

Spe Kingdom Of Saudi Arabia Annual Technical Symposium And Exhibition

Optimization of Infill Drilling in Whicher Range Field in Australia

machine learning

reservoir simulation

asset and portfolio management

cumulative production

transient drainage area

production rate

reservoir model

infill well

tight gas reservoir

Modeling & Simulation

Omar

Aswin R.

Md Mofazzal

Akim H.

...Show More Authors

AbstractNow that most of the conventional reservoirs are being depleted at a rapid pace, the focus is on unconventional reservoirs like tight gas reservoirs. Due to the heterogeneous nature and low permeability of unconventional reservoirs, they require a huge number of wells to hit all the isolated hydrocarbon zones. Infill drilling is one of the most common and effective methods of increasing the recovery, by reducing the well spacing and increasing the sweep efficiency. However, the problem with drilling such a large number of wells is the determination of the optimum location for each well that ensures minimum interference between wells, and accelerates the recovery from the field. Detail ... Show More

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