Resilience grant strand 2 for IUK project SHAIR - automated seismic interpretation using neural networks

SHAIR将创建一种新的软件服务，该服务将提供高精度的地震数据解释，以确定可能存在的石油或天然气。该项目的主要重点是开发新技术，利用业界领先的XWI算法，利用AI/ML提高地下成像的准确性和自动化程度。运行这些算法所需的计算能力是巨大的——已经使用了100万个虚拟cpu。S-Cube在SHAIR的合作伙伴挪威的RagnaRock Geo的技术目前包含人工智能驱动的地平线解释，人工解释最少。它采用地下体积，并使用改进的地球物理导向神经网络（gnn）卷积神经网络（cnn）的创新来检测岩石结构中的不连续面，并将其解释为“地平线”。S-Cube的技术XWI是从伦敦帝国理工学院一个世界领先的研究小组分离出来的，是20年发展的结果，拥有多项专利。它是传统全波形反演技术（FWI）的进步，可生成高质量的地下三维模型，有助于在钻井前评估地下特征。主要结果将是一套新的工具，作为SaaS产品提供给能源公司，用户将通过这些工具付费来更准确地分析他们的数据。这项新技术将增强现有的XWI算法，在自动生成地震层的约束下生成更好的速度模型。与传统的石油发现分析方法相比，这项新服务将使石油公司在增加储量和减少排放方面更具成本效益，同时也更准确。通过更好的分析和更高的成功率，能源公司将变得更加有利可图，并能够从石油转向低排放的地下能源的新来源。这种改进的数据解释可以减少钻探碳氢化合物的可能性，从而减少钻井数量，保护环境。

SHAIR will create a new software service that will deliver highly accurate interpretation of seismic data to determine the likely presence of oil or gas.The main focus of this project is to develop new technology for increasing the accuracy and automation for imaging the subsurface using AI/ML within an industry-leading algorithm known as XWI. The computational power needed to run these algorithms is massive -- exceptionally 1 million virtual CPUs have been used.Technology from S-Cube's partner in SHAIR, RagnaRock Geo from Norway, currently contains an AI driven horizon interpretation with minimal human interpretation. It takes in subsurface volumes and uses their improved Geophysics-guided Neural Networks (GNNs) innovation of Convolutional Neural Networks (CNNs) to detect discontinuities in the rock structure, and interprets these as 'horizons'.S-Cube's technology, XWI, spun out from a world leading research group from Imperial College London is the result of 20 years of development, covered by multiple patents. It is an advancement of traditional Full-Waveform Inversion (FWI) producing high quality 3D subsurface models useful in assessing subsurface features ahead of drilling.The main result will be a novel suite of tools available to energy companies as a SaaS product via which users will pay to more accurately analyse their data. The new technology will enhance existing XWI algorithms generating superior velocity models constrained using automatically-generated seismic horizons.This will be deployed as a new service that makes it more cost effective for oil companies to grow reserves and minimise emissions with more accuracy than the traditional method of analysis used to discover oil.Energy companies will become more profitable via better analysis and a higher rate of success and be able to diversify from petroleum to new sources of lower emissions subsurface energy. This improved interpretation of data should reduce the likelihood of drilling for hydrocarbons which results in none being found and therefore can help the environment with fewer wells drilled.