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

挑战者地质仪器加拿大有限公司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。该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，对油气公司控制运营成本至关重要，对保护加拿大的环境也很重要。实践证明，综合多种信息源确定钻井位置将显著提高钻井成功率。例如，在这一过程中，可以通过全波形反演(FWI)方法生成的高分辨率潜在油田的地下图像是非常重要的。另一方面，FWI存在着对初始模型敏感、计算量大等严重问题。 Challenger GeoInstruments Canada Ltd.拥有一支由地球物理学家组成的专业团队(其中大部分是APEGGA成员和博士)和技术人员，他们在石油和天然气勘探、采矿、环境和工程项目的各种地球物理方法方面拥有广泛的知识和经验。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关注FWI的计算方法和相关问题。最近我们取得了进展，开发了新的算法，这需要油田的真实地震数据来验证。此外，为了建立一个可靠的初始模型，我们需要高质量的测井数据分析，而这在我的研究组中是没有的。 我们将与挑战者地理仪器加拿大有限公司合作，结合我们的知识、专业知识和其他研究资源，开发一套完整的含油量预测工作流程。

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.