Technology Development in Iranian Petroleum Industry: Approaches, Achievements, and Challenges

2016 ◽  
pp. 87-110
Author(s):  
Fatemeh Hoshdar ◽  
Seyed Farhang Fassihi
Keyword(s):  
Technology Development ◽  
Petroleum Industry

THE IMPACT OF INTEGRATED RESERVOIR CHARACTERISATION ON THE BUSINESS PERFORMANCE OF THE MODERN PETROLEUM COMPANY

1997 ◽  
Vol 37 (1) ◽  
pp. 105
Author(s):  
A.A. Curtis ◽  
J.F. McCarthy ◽  
C. Balnaves
Keyword(s):  
Business Performance ◽  
Technology Development ◽  
Petroleum Industry ◽  
Computer Applications ◽  
Work Practices ◽  
Bottom Line ◽  
Cycle Times ◽  
Petroleum Companies ◽  
Petroleum Company ◽  
The Impact

One emerging technology that has the capacity to significantly improve the way the petroleum industry undertakes its business is reservoir characterisation. Compelling business drivers for the adoption of reservoir characterisation by petroleum companies exist, including the reduction of project risk, the optimisation of reservoir performance, and the improvement of work practices, all of which can lead to far shorter project cycle times and better financial performance. Integrated Reservoir Characterisation has been successfully applied by one petroleum company following the implementation of a project designed to promote its adoption. A process description of Integrated Reservoir Characterisation applicable to the company was developed and this was used in the evaluation of computer applications to implement the concepts. The implications for both reservoir technology development and for training are considerable, with the latter being addressed by the use of case studies. The impact that Integrated Reservoir Characterisation is having, and is likely to have, on the business in terms of work practices, the treatment of uncertainty, and on real time well operations is such that it will feature far more prominently in everyday data management and analysis, interpretation and decision making. Integrated Reservoir Characterisation is a 'core-of-the-business' technology that has the potential to yield substantial bottom-line benefits if it is successfully advanced within the modern petroleum company.

The Prospect of Application of Nanometer Material in Oil Exploitation

2012 ◽  
Vol 490-495 ◽  
pp. 3802-3806 ◽  
Author(s):  
Shi Dong Zhu ◽  
Jian Jun Zhang ◽  
Jun Feng Shi ◽  
Rui Dong Zhao ◽  
Meng Liu ◽  
...  
Keyword(s):  
Materials Science ◽  
Technology Development ◽  
Imaging System ◽  
Petroleum Industry ◽  
Original Material ◽  
Coating Technology ◽  
The Past ◽  
Leading Role ◽  
Oil Exploitation ◽  
Nanometer Material

Emerging of nanotechnology represents development and achievements of modern materials science. Petroleum industry nowadays plays a leading role in development of energy industry. Therefore, the combination of the two is a valuable research subject. The prospect of application of nanometer material in injection-production, tertiary oil production, well sensing and imaging system and coating technology is presented herein. In addition, issues with respect to application of nanometer material in oil exploitation are discussed. Nanometer material and nanotechnology is the frontier technology in science and technology development in the past decades. It is predicated that today's ordinary original material be replaced by nanometer material and nanotechnology be a "key technology"[1] that will surpass internet and genetic technology.

Some applications of electron beam microanalysis techniques in VLSI process evaluation

1983 ◽  
Vol 41 ◽  
pp. 160-161
Author(s):  
Simon Thomas
Keyword(s):  
Integrated Circuits ◽  
Process Evaluation ◽  
Large Scale ◽  
Technology Development ◽  
Analytical Techniques ◽  
Successful Implementation ◽  
Analysis Of Failures ◽  
Characterization Of Materials ◽  
Circuits Vlsi

Trends in the technology development of very large scale integrated circuits (VLSI) have been in the direction of higher density of components with smaller dimensions. The scaling down of device dimensions has been not only laterally but also in depth. Such efforts in miniaturization bring with them new developments in materials and processing. Successful implementation of these efforts is, to a large extent, dependent on the proper understanding of the material properties, process technologies and reliability issues, through adequate analytical studies. The analytical instrumentation technology has, fortunately, kept pace with the basic requirements of devices with lateral dimensions in the micron/ submicron range and depths of the order of nonometers. Often, newer analytical techniques have emerged or the more conventional techniques have been adapted to meet the more stringent requirements. As such, a variety of analytical techniques are available today to aid an analyst in the efforts of VLSI process evaluation. Generally such analytical efforts are divided into the characterization of materials, evaluation of processing steps and the analysis of failures.

High resolution electron microscopy of lanthanum phosphate crystals

1978 ◽  
Vol 36 (1) ◽  
pp. 274-275
Author(s):  
J. C. Wheatley ◽  
J. M. Cowley
Keyword(s):  
Electron Microscopy ◽  
Catalytic Activity ◽  
High Resolution ◽  
Petroleum Industry ◽  
High Resolution Electron Microscopy ◽  
Lanthanum Phosphate ◽  
Good Catalyst ◽  
Resolution Electron ◽  
Good Catalytic Activity ◽  
Physical And Chemical

Rare-earth phosphates are of particular interest because of their catalytic properties associated with the hydrolysis of many aromatic chlorides in the petroleum industry. Lanthanum phosphates (LaPO4) which have been doped with small amounts of copper have shown increased catalytic activity (1). However the physical and chemical characteristics of the samples leading to good catalytic activity are not known.Many catalysts are amorphous and thus do not easily lend themselves to methods of investigation which would include electron microscopy. However, the LaPO4, crystals are quite suitable samples for high resolution techniques.The samples used were obtained from William L. Kehl of Gulf Research and Development Company. The electron microscopy was carried out on a JEOL JEM-100B which had been modified for high resolution microscopy (2). Standard high resolution techniques were employed. Three different sample types were observed: 669A-1-5-7 (poor catalyst), H-L-2 (good catalyst) and 27-011 (good catalyst).

Models of Development Based on Technology Diffusion

2012 ◽  
pp. 117-131 ◽  
Author(s):  
O. Golichenko
Keyword(s):  
Knowledge Transfer ◽  
Technology Diffusion ◽  
Technology Development ◽  
International Competition ◽  
Global Knowledge ◽  
Technology Knowledge ◽  
Catching Up ◽  
Technological Potential ◽  
Models Of Development ◽  
Effective Use

The problems of multifold increase of technological potential of developing countries are considered in the article. To solve them, i.e. to organize effectively tapping into global knowledge and their absorption, the performance of two diffusion channels is considered: open knowledge transfer and commercial knowledge transfer. The models of technological catching-up are investigated. Two of them are found to give an opportunity of effective use of international competition and global technology knowledge as a driver of technology development.

Machine Learning Verdict of EEG Signals in Brain Computer Interface

2018 ◽  
pp. 429-441
Author(s):  
M. Jeyanthi ◽  
C. Velayutham
Keyword(s):  
Nearest Neighbor ◽  
Technology Development ◽  
Vital Role ◽  
Svm Classifier ◽  
K Nearest Neighbor ◽  
Data Mining Technique ◽  
Data Set ◽  
Eeg Data ◽  
Irrelevant Attributes

In Science and Technology Development BCI plays a vital role in the field of Research. Classification is a data mining technique used to predict group membership for data instances. Analyses of BCI data are challenging because feature extraction and classification of these data are more difficult as compared with those applied to raw data. In this paper, We extracted features using statistical Haralick features from the raw EEG data . Then the features are Normalized, Binning is used to improve the accuracy of the predictive models by reducing noise and eliminate some irrelevant attributes and then the classification is performed using different classification techniques such as Naïve Bayes, k-nearest neighbor classifier, SVM classifier using BCI dataset. Finally we propose the SVM classification algorithm for the BCI data set.

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