An integrated workflow for oil-bearing prediction using seismic information and well log data

Challenger Geoinstruments Canada Ltd. 是一家总部位于卡尔加里的公司，为石油和天然气行业提供高质量的陆上、浅水和井下地震服务。公司的核心服务包括地球物理咨询、地震数据处理、解释和测井数据分析。提高钻井成功率是一项具有挑战性的任务，这对于石油和天然气公司控制运营成本至关重要，对于保护加拿大的环境也很重要。事实证明，结合多种信息源来确定钻井位置将显着提高成功率。例如，通过全波形反演（FWI）方法创建潜在油田的高分辨率地下图像在此过程中非常重要。另一方面，FWI 也面临着初始模型敏感、计算成本高等严重问题。 Challenger Geoinstruments Canada Ltd. 拥有一支由地球物理学家（大部分是 APEGGA 会员和博士）和技术人员组成的专业团队，他们在石油和天然气勘探、采矿、环境和工程项目的地球物理方法方面拥有丰富的知识和经验。然而，他们缺乏 FWI 方面的专业知识和经验。我在卡尔加里大学的研究小组主要研究 FWI 的计算方法及相关问题。最近我们取得了进展并开发了新的算法，这需要来自油田的真实地震数据进行验证。此外，为了建立可靠的初始模型，我们需要高质量的测井数据分析，而这是我的研究小组所不具备的。 我们将与 Challenger Geoinstruments Canada Ltd. 合作，结合我们的知识、专业知识和其他研究资源，开发含油预测的集成工作流程。

Challenger Geoinstruments Canada Ltd. is a Calgary-based Company which provides high quality onshore, shallow water and down hole seismic services to the oil and gas industry. The core services of the company include geophysical consulting, seismic data processing, interpretation and well log data analysis. Improving well-drilling success rate is a challenging task, which is critical for oil and gas company to control operational cost, and important to protect Canada's environment. It has been shown that combining multiple sources of information to determine the well-drilling location will significantly enhance the success rate. For example, a high-resolution subsurface image of the potential oil field, which can be created through full waveform inversion (FWI) method, is of great importance in this process. On the other hand, FWI suffers from severe issues such as sensitivity on the initial model and high computational cost. Challenger Geoinstruments Canada Ltd. has a professional team of geophysicists (most of them are APEGGA Members and PhDs) and technicians with extensive knowledge and experience in a broad range of geophysical methods for oil and gas exploration, mining, environmental and engineering projects. However, they lack expertise and experiences in FWI. My research group at the University of Calgary mainly focuses on computational methods for FWI and related problems. Recently we have made progress and developed new algorithms, which require real seismic data from oil fields for validation. Moreover, to build a reliable initial model, we need high-quality well-log data analysis, which is not available in my research group. We will collaborate with Challenger Geoinstruments Canada Ltd. to develop an integrated workflow for oil-bearing prediction by combining our knowledge, expertise and other research resources.