Smart Logging – An Innovative Approach for Generation of Digital Subsurface Data: 55-62

Abstract

Ground investigation (GI) to collect subsurface data is one of the crucial parts of engineering projects. With the rapid development of digital technology, 3-D and BIM applications have widely been adopted in these projects. To meet the current demand for real-time generation and dissemination of digital subsurface data, it is necessary to explore ways to enhance the production of the GI data to support these applications. Traditionally, project engineers or engineering geologists make use of the data in the GI records to produce geological models, by hand or using Computer Aided Design (CAD). Recently, computer software to extract digital AGS data to form 3-D ground models becomes more important. The requirement for preparing the AGS disks was introduced to GI term contracts administered by the Geotechnical Engineering Office (GEO) of the Civil Engineering and Development Department (CEDD) in 1993. Most Government contracts have also adopted similar requirements for AGS data. The reports and the corresponding AGS disks are kept in the Geotechnical Information Unit (GIU) of the Civil Engineering Library (CEL). Currently, over 210,000 sets of GI data in AGS format are kept in the CEL. It takes some time after completion of GI fieldwork before project engineers or engineering geologists can obtain the GI logs under the current arrangement. Since most engineering projects have very tight programmes, there is a need to explore ways to streamline this procedure. In addition, during production of geological logs, the logs done by logging geologists and other site staff need to be transferred to digital format and such work involves substantial resources and time, and sometimes may introduce unnecessary errors. To tackle the above issues, a ‘Smart Logging’ approach which makes use of mobile handheld devices for inputting and uploading GI data to establish geological models in a real-time manner is proposed. Under this arrangement, geologists and site staff can use a mobile handheld device to input geological and other GI data. Project engineers or engineering geologists are able to download the GI data to establish or refine their geological models as soon as the logging is completed. This greatly improves the efficiency of the study works. In addition, an artificial Intelligence (AI) tool has recently been developed and can be integrated into the Smart Logging app. Such AI tool can provide a useful check of the GI logs done by field personnel to reduce human errors. A feasibility study has recently been conducted and the result is promising. This paper presents the principle, methodology and way forward of this innovative Smart Logging approach for generation of digital subsurface data.