1st Iran InterPore Conference

Session

Parallel Session 8

IIPC04

25 Sept 2024, 11:00

School of Mechanical Engineering, University of Tehran

Conveners

Parallel Session 8: Digital Rocks / Machine Learning

• Alireza Fathollahi (University of Tehran)

37. Smart Proxy Model Development for foam injection in a fractured carbonate reservoir for Enhanced Oil Recovery

Ms Hamdam Majd Teymouri (sahand university of technology)

25/09/2024, 11:00

Digital Rocks / Machine Learning

Oral Presentation

Most of the world's oil reservoirs are carbonate and are often in the secondary stage of production. Foam injection could be a highly effective method for improving displacement efficiency, increasing production rates, and enhancing oil recovery mainly by reducing issues like fingering and channeling during gas-injection based processes. In this study, a fractured carbonate reservoir was...

40. تخمین تراوایی نسبی سنگ مخزن ناهمسانگرد با استفاده از پردازش داده دیجیتال

Mr Ahmed Zoeir (Shiraz University)

25/09/2024, 11:15

Digital Rocks / Machine Learning

Oral Presentation

چكيده
در این مقاله با حل همزمان قانون دارسی و معادله استوکس به محاسبه تراوایی نسبی سه فازی پرداختیم. برای انجام محاسبات ابتدا شبکه حفرات به هم پیوسته از داده سی تی اسکن استخراج و توزیع سیالات درون حفرات در جریان دو فازی پیش بینی شد. سپس با استفاده از معادلات پیوستگی و مومنتوم به محاسبه توزیع فشار هر یک از فاز ها در شبکه حفرات پرداخته شد. در ادامه، دبی جریان عبوری و فشار دیفرانسیلی پیرامون برش...

53. Application of statistical analysis of CBCT images in evaluation of rock heterogeneity of hydrocarbon reservoirs and reservoir studies

Shirin Samani (Shiraz University)

25/09/2024, 11:30

Digital Rocks / Machine Learning

Oral Presentation

Investigating changes in the reservoir rock's pore system during multiphase flow studies in porous media is crucial, especially for processes like enhanced oil recovery, underground carbon dioxide storage, and wastewater disposal. Ignoring core heterogeneity in laboratory studies can significantly impact the results and their potential for upscaling to the reservoir.
In this study, 31...

62. Generating Images of Naturally Fractured Carbonate Reservoir Rocks Using Deep Learning Architecture

Behrad Tabrizipour

25/09/2024, 11:45

Digital Rocks / Machine Learning

Oral Presentation

Carbonated reservoirs is one of the most usable and common reservoirs in throughout the world, especially in the middle east, and it is challenging to predict the fractures in these reservoirs. Generative adversarial networks (GAN) and Autoencoders can generate or create different purposes based on needs using images among different types of artificial intelligence algorithms. Powerful and...