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Record W4232540886 · doi:10.2523/93779-ms

The Role of Unconventional Natural Gases in the Next 30 Years in Asia

2005· article· en· W4232540886 on OpenAlexaboutno aff
Daijiro Terasaki, Kazuo Fujita

Bibliographic record

VenueProceedings of SPE Asia Pacific Oil and Gas Conference and Exhibition · 2005
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsnot available
Fundersnot available
KeywordsExhibitionCitationNatural gasLibrary scienceFujita scaleComputer scienceEngineeringOperations researchGeographyArchaeologyMeteorologyWaste management

Abstract

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The Role of Unconventional Natural Gases in the Next 30 Years in Asia Daijiro Terasaki; Daijiro Terasaki Tokyo Gas Co., Ltd. Search for other works by this author on: This Site Google Scholar Kazuo Fujita Kazuo Fujita Sibaura Institute of Technology Search for other works by this author on: This Site Google Scholar Paper presented at the SPE Asia Pacific Oil and Gas Conference and Exhibition, Jakarta, Indonesia, April 2005. Paper Number: SPE-93779-MS https://doi.org/10.2118/93779-MS Published: April 05 2005 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Terasaki, Daijiro, and Kazuo Fujita. "The Role of Unconventional Natural Gases in the Next 30 Years in Asia." Paper presented at the SPE Asia Pacific Oil and Gas Conference and Exhibition, Jakarta, Indonesia, April 2005. doi: https://doi.org/10.2118/93779-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu nav search search input Search input auto suggest search filter All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE Asia Pacific Oil and Gas Conference and Exhibition Search Advanced Search AbstractGenetic algorithm method was utilized to study on the optimum supply rates of various types of natural gases for the importing countries such as China, India and Japan. Genetic algorithm procedure was able to compute annual time series of economically optimum supply rates combination consisting individual natural gases so that net present value of total supply costs could be minimized to result in economic optimization.First of all, several computations for USA case history data matching were carried out to establish appropriate parameters of genetic algorithm, because USA has long term historical data provided by DOE/EIA and USGS about natural gas production activities and has the infrastructures of gas pipelines fully furnished.Next, computations for the whole region of Asia, Oceania and the Middle East based on the forecast of total demand by OECD/IEA were carried out, and then individual computation for China, India and Japan was carried out in the same way. It was concluded that unbalance between the demand and the supply of natural gases would occur in Asia, and unconventional natural gases especially coal-bed methane would play an important role both to satisfy stable natural gas demand, and to keep national security on energy in the next 30 years in Asia, especially China and India countries.1. IntroductionNatural gases are now thought to be important energy resources in the 21st century because they are widely distributed in the world and the amount of carbon dioxide discharge from their burning is the least among the fossil fuels. As for the world demand of natural gas, the average growth rate of 2.4% is predicted up to 2030, namely it increases from 2,527 bcm in 2000 to 5,047 bcm in 2030 [19]. It is considered that the demand of natural gas in Asian region, especially China, and Latin America region will grow rapidly. In 2000, the commercial production of natural gas was 2390 bcm (about 84.4 tcf) in which the international gas trade was 526.2 bcm, which was equivalent to only 22% of the world. The pipeline gas trade is 389 bcm, which was equivalent to 76% of the international trade, and the remaining is LNG trade, which amounts to 137 bcm. It is difficult to transport natural gas over the long distance, so that gas trades are often carried out in the specific region thus gas trades with the outside of the region is limited only less than 10%. Because international long distance pipelines are not yet constructed in Asia, Oceania and the Middle East regions, LNG transport occupies 95.9% of the natural gas trade, which is rather expensive. Therefore the most important subject in natural gas trade in this region is to reduce the transport cost.In future, even if it is realized that the long distance main pipelines are constructed to the big consumption areas such as China and India in order to transport natural gases of the Central Asia and the East Siberia regions, it is presumed that the reduction of transport cost becomes important subject. In these regions, if the production cost of unconventional natural gases would decrease according to the technological innovation, they could compete with the imported LNG because transport costs of them through pipelines may be much lower than the imported LNG. In the region where the demand of natural gas can't be fulfilled with the conventional gas, it may be happened to produce unconventional gases commercially. Under such circumstances, the purpose of our study is to predict the optimum allocation of supply rates for individual natural gases in Asia region so that the total cost of production and transportation is minimized.Referring to the actual results and the future production forecast of the natural gases in North America region including USA and Canada, the beginning of commercial production and the successive quantitative change of unconventional natural gases in Asian region are studied. They change diachronically by the factor such as the market price, the production cost, the transport system and cost. It is presumed that the genetic algorithm is suitable for the non-liner optimization problems such as simulating behavior where many factors interrelate to the mutuality depending upon time steps. The genetic algorithm is compared with Quasi-Newton method, and more suitable one will be applied to predict the production allocation of natural gases. The purpose of our simulation is to find the optimum supply rate of each natural gas such as conventional gas, tight sand gas, coal-bed methane and shale gas. Keywords: unconventional natural gas, japan, artificial intelligence, machine learning, recoverable resource, oceania, gas monetization, asia, supply cost, middle east Subjects: Pipelines, Flowlines and Risers, Natural Gas Conversion and Storage, Unconventional and Complex Reservoirs, Information Management and Systems, Liquified natural gas (LNG) This content is only available via PDF. 2005. Society of Petroleum Engineers You can access this article if you purchase or spend a download.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.854
Threshold uncertainty score0.218

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.233
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2005
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