Using Artificial Intelligence to Solve Complex Flow Equations in a Wet Gas Environment

使用人工智能求解湿气体环境中的复杂流量方程

• 批准号: 10091110
• 金额: $ 1.39万
• 依托单位: GM FLOW MEASUREMENT SERVICES LTD
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2024
• 资助国家: 英国
• 起止时间: 2024 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10091110
• 关键词: Using; Artificial; Intelligence; Solve; Complex

GM Flow and Astute are working on this project will develop artificial intelligence based software, to enhance an automated self-adjusting differential pressure cone-type flow meter, for continuous and very accurate wet gas metering.The existing flow meter has an industry leading operating flow range, making it the preferred choice for dry gas flow measurement. It has definite potential to be a wet gas flow meter, capable of accurately measuring gas flow with a liquid content.To explore this potential, we have extensively modelled and flow loop tested the meter using computational fluid dynamics and have undertaken field trials in multiple gas wells in Saudi Arabia.This project aims to conduct an extensive wet gas physical testing program. By investigating various parameters such as water-cut, gas wetness, flow rate, and flowing pressures, we will generate comprehensive performance data. This extensive dataset will to be analysed and software will be developed to enable continuous assessment of data and the application of real-time operating parameter corrections, on commercial gas well applications.To efficiently handle this vast amount of data, we will leverage the power of artificial intelligence. In collaboration with the Astute Centre of Excellence we will generate and then apply new algorithms, so we can quickly analyse ongoing gas production data relative to reference data, identify the most suitable reference data points for specific production conditions, and instantly correct flow measurements.This cutting-edge approach will save time, ensure data accuracy, and establish the automated self-adjusting cone-type flow meter as the preferred choice for wet gas metering globally. This continuous data acquisition and real-time monitoring will reduce or even eliminate the need for periodic and costly well testing, helping optimise gas well management practices. The results of this project will be a significant milestone in the oil and gas industry's evolution of more efficient and accurate flow measurement technologies.

GM Flow和Astute正在开发基于人工智能的软件，以增强自动自调节压差锥形流量计，用于连续和非常准确的湿气计量。现有流量计具有行业领先的工作流量范围，使其成为干气流量测量的首选。它有一定的潜力成为湿气流量计，能够精确测量含液体的气体流量。为了探索这种潜力，我们使用计算流体力学对该流量计进行了广泛的建模和流动回路测试，并在沙特阿拉伯的多口威尔斯气井进行了现场试验。该项目旨在进行广泛的湿气物理测试计划。通过研究含水率、气体湿度、流量和流动压力等各种参数，我们将生成综合性能数据。我们将对这一广泛的数据集进行分析，并开发软件，以便在商业气井应用中持续评估数据并应用实时操作参数校正。为了有效处理这一海量数据，我们将利用人工智能的力量。通过与Astute卓越中心的合作，我们将生成并应用新的算法，以便快速分析与参考数据相关的持续天然气生产数据，确定特定生产条件下最合适的参考数据点，并立即校正流量测量值。这种尖端方法将节省时间，确保数据准确性，确立了全自动自调锥式流量计为全球湿气计量的首选。这种连续的数据采集和实时监控将减少甚至消除对定期和昂贵的试井的需求，有助于优化气井管理实践。该项目的成果将成为石油和天然气行业发展更高效、更准确的流量测量技术的重要里程碑。