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contributor authorShi, Mingyu
contributor authorZhang, Fengyuan
contributor authorLu, Ruihan
contributor authorCao, Wenxing
contributor authorLiu, Xia
contributor authorLiu, Weidian
contributor authorLiu, Dianyu
date accessioned2025-04-21T10:14:20Z
date available2025-04-21T10:14:20Z
date copyright1/21/2025 12:00:00 AM
date issued2025
identifier issn2998-1638
identifier otherjertb_1_2_021008.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4305772
description abstractDue to recent oil price fluctuations, oil companies have optimized assets and promoted joint ventures, leading to a need for fast, accurate oilfield asset evaluation, including development and growth costs. Oilfield development costs are dynamically influenced by internal and macroeconomic factors. Using big data analysis with a eviews economic analysis software owned by IHS (E-VIEW), a model was developed to analyze cost influencers. Research on nine main factors showed strong scientific correlations, linking expansion costs with market indexes. This provides technical support for more efficient and accurate cost estimations and predictions of oilfield assets.
publisherThe American Society of Mechanical Engineers (ASME)
titleStudy of Oilfield Development Cost Market Index Modeling Based on Big Data
typeJournal Paper
journal volume1
journal issue2
journal titleJournal of Energy Resources Technology, Part B: Subsurface Energy and Carbon Capture
identifier doi10.1115/1.4067547
journal fristpage21008-1
journal lastpage21008-8
page8
treeJournal of Energy Resources Technology, Part B: Subsurface Energy and Carbon Capture:;2025:;volume( 001 ):;issue: 002
contenttypeFulltext


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