Preferred Language
Articles
/
7hiURpcBVTCNdQwCM5ZM
Reservoir permeability prediction based artificial intelligence techniques
...Show More Authors

   Predicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes beyond simply predicting lithology to provide a detailed quantification of primary minerals (e.g., calcite and dolomite) as well as secondary ones (e.g., shale and anhydrite). The results show important lithological contrast with the high-porosity layers correlating to possible reservoir areas. The richness of Quanti-Elan's interpretations goes beyond what log analysis alone can reveal. The methodology is described in-depth, discussing the approaches used to train neural networks (e.g., data processing, network architecture). A case study where output of neural network predictions of permeability in a particular oil well are compared with core measurements. The results indicate an exceptional closeness between predicted and actual values, further emphasizing the power of this approach. An extrapolated neural network model using lithology (dolomite and limestone) and porosity as input emphasizes the close match between predicted vs. observed carbonate reservoir permeability. This case study demonstrated the ability of neural networks to accurately characterize and predict permeability in complex carbonate systems. Therefore, the results confirmed that neural networks are a reliable and transformative technology tool for oil reservoirs management, which can help to make future predictive methodologies more efficient hydrocarbon recovery operations.

Crossref
View Publication
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
...Show More Authors
Abstract<p>Geomechanical 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</p> ... Show More
View Publication
Scopus (11)
Crossref (8)
Scopus Clarivate Crossref
Publication Date
Wed May 05 2021
Journal Name
Journal Of Petroleum Research And Studies
The Role of Chemistry of the Oil-Field Water in the Distribution of Reservoir Pressures: A Case Study of Mishrif Reservoir in the Southern Oil-Fields, Iraq
...Show More Authors

Mishrif Formation is the main reservoir in oil-fields (North Rumaila, South Rumaila, Majnoon, Zubair and West Qurna) which located at Basrah southern Iraq. The Inductively coupled plasma-Mass spectrometer (ICP-MS) was used for the water chemistry analysis and Scanning Electron Microprobe (SEM) for the purpose of mineralogy diagnosis. A weak acidic water of salinity six-time greater than seawater plays a role in generating the formation pressure and controlling the fluid flow. The potentiometric subsurface maps were modeled and the direction of super-pressure sites that are of a great importance in the oil exploration were marked to pay attention during future drilling.

View Publication
Crossref
Publication Date
Thu Jan 31 2019
Journal Name
Journal Of Engineering
Estimation of Cutoff Values by Using Regression Lines Method in Mishrif Reservoir/ Missan oil Fields
...Show More Authors

Net pay is one of the most important parameters used in determining initial oil in place of a reservoir. It can be delineated through the using of limiting values of the petrophysical properties of the reservoir. Those limiting values are named as the cutoff. This paper provides an insight into the application of regression line method in estimating porosity, clay volume and water saturation cutoff values in Mishrif reservoir/ Missan oil fields. The study included 29 wells distributed in seven oilfields of Halfaya, Buzurgan, Dujaila, Noor, Fauqi, Amara and Kumait.

This study is carried out by applying two types of linear regressions: Least square and Reduce Major Axis Regression.

The Mishrif formation was

... Show More
View Publication Preview PDF
Crossref (4)
Crossref
Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Engineering
Convolutional Multi-Spike Neural Network as Intelligent System Prediction for Control Systems
...Show More Authors

The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed

... Show More
View Publication Preview PDF
Crossref (1)
Crossref
Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Developing Arabic License Plate Recognition System Using Artificial Neural Network and Canny Edge Detection
...Show More Authors

            In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the

... Show More
View Publication Preview PDF
Scopus (10)
Crossref (5)
Scopus Clarivate Crossref
Publication Date
Wed Feb 01 2023
Journal Name
Journal Of Engineering
Vertical Stress Prediction for Zubair Oil Field/ Case Study
...Show More Authors

Predicting vertical stress was indeed useful for controlling geomechanical issues since it allowed for the computation of pore pressure for the formation and the classification of fault regimes. This study provides an in-depth observation of vertical stress prediction utilizing numerous approaches using the Techlog 2015 software. Gardner's method results in incorrect vertical stress values with a problem that this method doesn't start from the surface and instead relies only on sound log data. Whereas the Amoco, Wendt non-acoustic, Traugott, average technique simply needed density log as input and used a straight line as the observed density, this was incorrect for vertical computing stress. The results of these methods

... Show More
View Publication Preview PDF
Crossref (1)
Crossref
Publication Date
Thu Sep 30 2010
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
PREDICTION OF FINITE CONCENTRATIONBEHAVIOR FROM INFINITE DILUTION EGUILIBRIUM DATA
...Show More Authors

Experimental activity coefficients at infinite dilution are particularly useful for calculating the parameters needed in an expression for the excess Gibbs energy. If reliable values of γ∞1 and γ∞2 are available, either from direct experiment or from a correlation, it is possible to predict the composition of the azeotrope and vapor-liquid equilibrium over the entire range of composition. These can be used to evaluate two adjustable constants in any desired expression for G E. In this study MOSCED model and SPACE model are two different methods were used to calculate γ∞1 and γ∞2

View Publication Preview PDF
Publication Date
Fri Apr 01 2022
Journal Name
Civil Engineering Journal
Prediction of Urban Spatial Changes Pattern Using Markov Chain
...Show More Authors

Urban land uses of all kinds are the constituent elements of the urban spatial structure. Because of the influence of economic and social factors, cities in general are characterized by the dynamic state of their elements over time. Urban functions occur in a certain way with different spatial patterns. Hence, urban planners and the relevant urban management teams should understand the future spatial pattern of these changes by resorting to quantitative models in spatial planning. This is to ensure that future predictions are made with a high level of accuracy so that appropriate strategies can be used to address the problems arising from such changes. The Markov chain method is one of the quantitative models used in spatial planning to ana

... Show More
View Publication
Scopus (22)
Crossref (15)
Scopus Clarivate Crossref
Publication Date
Mon Oct 29 2018
Journal Name
International Journal Of Women's Health And Reproduction Sciences
Prediction of Placenta Accreta Using Hyperglycosylated Human Chorionic Gonadotropin
...Show More Authors

Objectives: Hyperglycosylated human chorionic gonadotropin (hCG) is a variant of hCG. In addition, it has a different oligosaccharide structure compared to the regular hCG and promotes the invasion and differentiation of peripheral cytotrophoblast. This study aimed to measure hyperglycosylated hCG as a predictor in the diagnosis of placenta accreta. Materials and Methods: In general, 90 pregnant women were involved in this case-control study among which, 30 ladies (control group) were pregnant within the gestational age of ≥36 weeks with at least one previous caesarean section and a normal sited placenta in transabdominal ultrasound (TAU). The other 60 pregnant women (case

... Show More
View Publication Preview PDF
Scopus (2)
Scopus Clarivate Crossref
Publication Date
Sat Jan 01 2022
Journal Name
Proceedings Of International Conference On Computing And Communication Networks
Automatic Health Speech Prediction System Using Support Vector Machine
...Show More Authors

View Publication
Scopus (3)
Scopus Clarivate Crossref