Preferred Language
Articles
/
gRd-Qo8BVTCNdQwCzmef
AVO analysis for high amplitude anomalies using 2D pre-stack seismic data
...Show More Authors

Amplitude variation with offset (AVO) analysis is an 1 efficient tool for hydrocarbon detection and identification of elastic rock properties and fluid types. It has been applied in the present study using reprocessed pre-stack 2D seismic data (1992, Caulerpa) from north-west of the Bonaparte Basin, Australia. The AVO response along the 2D pre-stack seismic data in the Laminaria High NW shelf of Australia was also investigated. Three hypotheses were suggested to investigate the AVO behaviour of the amplitude anomalies in which three different factors; fluid substitution, porosity and thickness (Wedge model) were tested. The AVO models with the synthetic gathers were analysed using log information to find which of these is the controlling parameter on the AVO analysis. AVO cross plots from the real pre-stack seismic data reveal AVO class IV (showing a negative intercept decreasing with offset). This result matches our modelled result of fluid substitution for the seismic synthetics. It is concluded that fluid substitution is the controlling parameter on the AVO analysis and therefore, the high amplitude anomaly on the seabed and the target horizon 9 is the result of changing the fluid content and the lithology along the target horizons. While changing the porosity has little effect on the amplitude variation with offset within the AVO cross plot. Finally, results from the wedge models show that a small change of thickness causes a change in the amplitude; however, this change in thickness gives a different AVO characteristic and a mismatch with the AVO result of the real 2D pre-stack seismic data. Therefore, a constant thin layer with changing fluids is more likely to be the cause of the high amplitude anomalies.

Scopus Clarivate Crossref
View Publication
Publication Date
Thu Mar 01 2012
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The Commitment of Public Companies in disclosure requirement of Financial Statement: Analysis Study in State Company for Leather Industries (SCLI)
...Show More Authors

It has been an increase concern of scientific and professional accounting sides on disclosure especially after appearance of business firms and accounting development with its relationship to financial statements which are considered to be outputs of the activity results.  The preparing of financial statements and auditing of those accounts according to normal principles and standards of accounting on both local and international levels. Accounting disclosure can be seen an importance through discover all fundamental and necessary information for proper supply. Therefore, the research will highlight on public companies commitment in Iraq for basis and standards which have taken disclosure in financial data. The conceptual frame of t

... Show More
View Publication Preview PDF
Publication Date
Sun Mar 31 2024
Journal Name
Iraqi Geological Journal
Permeability Prediction and Facies Distribution for Yamama Reservoir in Faihaa Oil Field: Role of Machine Learning and Cluster Analysis Approach
...Show More Authors

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

... Show More
View Publication
Scopus (7)
Crossref (3)
Scopus Crossref
Publication Date
Fri Jul 10 2020
Journal Name
Int. J. Agricult. Stat. Sci
STUDY EVALUATION AND ANALYSIS OF THE PROPERTIES OF SOME PERFORMANCE STANDARDS FOR AGRICULTURAL TRACTOR AND SORGHUM BICOLOR (L.) MOENCH YIELD
...Show More Authors

A field experiment was conducted in an agricultural field in Al-Hindia district, Karbala governorate in a silty clay soil during the year 2020. The research included a study of two factors, the first is the depth of plowing at two levels, namely 13 and 20 cm, which represented the main blocks. The second is the tire inflation pressure at two levels, namely (70 and 140 kPa), which represented the secondary blocks. Slippage percentage, field efficiency, leaf area, and 300 grain weight were studied. The experiment was carried out using a split-plot system under a Randomized complete block design, at three replications. The tillage depth of 13 cm exceeds/transcend by giving it the least slippage of (11.01%), the highest field efficiency of (50.

... Show More
Publication Date
Tue Mar 01 2016
Journal Name
Journal Of Natural Sciences Research
Spectrophotometric-Assisted Chemometric Method for the Simultaneous Analysis of Furosemide, Carbamazepine, Diazepam, and Carvedilol in Their Bulk and Marketed Formulation
...Show More Authors

Simultaneous determination of Furosemide, Carbamazepine, Diazepam, and Carvedilol in bulk and pharmaceutical formulation using the partial least squares regression (PLS-1 and PLS-2) is described in this study. The two methods were successfully applied to estimate the four drugs in their quaternary mixture using UV spectral data of 84synthetic mixtures in the range of 200-350nm with the intervals Δλ=0.5nm. The linear concentration range were 1-20 μg.mL-1 for all, with correlation coefficient (R2) and root mean squares error for the calibration (RMSE) for FURO, CARB, DIAZ, and CARV were 0.9996, 0.9998, 0.9997, 0.9997, and 0.1128, 0.1292, 0.1868,0.1562 respectively for PLS-1, and for PLS-2 were 0.9995, 0.9999, 0.9997, 0.9998, and 0.1127, 0.

... Show More
Publication Date
Sat Feb 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Revealing the potentials of 3D modelling techniques; a comparison study towards data fusion from hybrid sensors
...Show More Authors
Abstract<p>The vast advantages of 3D modelling industry have urged competitors to improve capturing techniques and processing pipelines towards minimizing labour requirements, saving time and reducing project risk. When it comes to digital 3D documentary and conserving projects, laser scanning and photogrammetry are compared to choose between the two. Since both techniques have pros and cons, this paper approaches the potential issues of individual techniques in terms of time, budget, accuracy, density, methodology and ease to use. Terrestrial laser scanner and close-range photogrammetry are tested to document a unique invaluable artefact (Lady of Hatra) located in Iraq for future data fusion sc</p> ... Show More
View Publication
Scopus (12)
Crossref (7)
Scopus Clarivate Crossref
Publication Date
Tue Oct 08 2002
Journal Name
Iraqi Journal Of Laser
Design Considerations of Laser Source in a Ring Network Based on Fiber Distributed Data Interface (FDDI)
...Show More Authors

This work presents the use of laser diode in the fiber distributed data interface FDDI networks. FDDI uses optical fiber as a transmission media. This solves the problems resulted from the EMI, and noise. In addition it increases the security of transmission. A network with a ring topology consists of three computers was designed and implemented. The timed token protocol was used to achieve and control the process of communication over the ring. Nonreturn to zero inversion (NRZI) modulation was carried out as a part of the physical (PHY) sublayer. The optical system consists of a laser diode with wavelength of 820 nm and 2.5 mW maximum output power as a source, optical fiber as a channel, and positive intrinsic negative (PIN) photodiode

... Show More
View Publication Preview PDF
Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Business, Communication &amp; Technology
Exploring the Adoption of Big Data Analytics in the Oil and Gas Industry: A Case Study
...Show More Authors

The oil and gas industry relies heavily on IT innovations to manage business processes, but the exponential generation of data has led to concerns about processing big data, generating valuable insights, and making timely decisions. Many companies have adopted Big Data Analytics (BDA) solutions to address these challenges. However, determining the adoption of BDA solutions requires a thorough understanding of the contextual factors influencing these decisions. This research explores these factors using a new Technology-Organisation-Environment (TOE) framework, presenting technological, organisational, and environmental factors. The study used a Delphi research method and seven heterogeneous panelists from an Oman oil and gas company

... Show More
View Publication Preview PDF
Crossref (1)
Crossref
Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
A Study on Transportation Models in Their Minimum and Maximum Values with Applications of Real Data
...Show More Authors

The purpose of this paper is to apply different transportation models in their minimum and maximum values by finding starting basic feasible solution and finding the optimal solution. The requirements of transportation models were presented with one of their applications in the case of minimizing the objective function, which was conducted by the researcher as real data, which took place one month in 2015, in one of the poultry farms for the production of eggs

... Show More
View Publication Preview PDF
Crossref
Publication Date
Sun May 01 2011
Journal Name
Information Sciences
Design and implementation of a t-way test data generation strategy with automated execution tool support
...Show More Authors

View Publication
Scopus (68)
Crossref (52)
Scopus Clarivate Crossref
Publication Date
Fri Apr 14 2023
Journal Name
Journal Of Big Data
A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
...Show More Authors
Abstract<p>Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for</p> ... Show More
View Publication Preview PDF
Scopus (628)
Crossref (628)
Scopus Clarivate Crossref