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  3. 亿级以上网格油藏模型三维可视化
OpenAtomGeneral MLAdvancedRegistration unverified

亿级以上网格油藏模型三维可视化

A advanced general ml competition requiring roughly 25–70 hours for an end-to-end practice run.

Difficulty
Advanced
Estimated effort
25–70 hours
Registration deadline
To be confirmed
Compute
CPU only
OverviewPreparationSource

Overview

Who this competition fits

Advanced practitioners with experience in general machine learning. Requires strong technical foundations and comfort with complex ML pipelines.

Read the original official blurb
本次竞赛的目标是期望实现亿级以上网格油藏模型流畅的三维显示和数据交互。通过应用先进的计算机图形技术,利用局部更新、按需加载、并行处理等技巧改进算法,实现亿级以上网格油藏模型流畅的三维显示和数据交互,助力HiSim软件的升级。 Official category: 实战竞技赛. Organizers: 中国石油天然气股份有限公司勘探开发研究院. Participants: 5.

Preparation

From registration to a first submission

  1. 01

    Python

  2. 02

    scikit-learn or similar ML library

  3. 03

    data analysis with pandas

Before you commit: Requires solid machine learning fundamentals and good experimental methodology. The competitive landscape is strong, with many experienced teams.

Source

How this page was assembled

Competition information is structured from the official page. Scores are platform estimates for decision support; official rules take precedence.

Official competition page
OpenAtom
Last checked
Sep 24, 2024

Entry assessment

est.
17

Prepare before joining

Overall fit estimate

Beginner fit17/100
Learning value66/100

Confirm eligibility and time commitment before moving into formal preparation.

Entry eligibility needs official confirmation

Open official pageSign in to saveOpen guide

Data and review state

Separate what is confirmed from what still needs review. Official rules and deadlines win.

View data stateClose
Source page verifiedMetric confirmedReviewed
Source published
Sep 24, 2024
Source created
Sep 24, 2024
Published on this site
Aug 1, 2026

Official metric is not published on the OpenAtom competition listing; verify scoring on the competition page.

reward_value_usd is a rough CNY→USD estimate (×0.14) for ranking only; use reward_summary for the official prize text.