a b s t r a c tLight Detection and Ranging (LiDAR) and Structure from Motion (SfM) provide large amounts of digital data from which virtual outcrops can be created. The accuracy of these surface reconstructions is critical for quantitative structural analysis. Assessment of LiDAR and SfM methodologies suggest that SfM results are comparable to high data-density LiDAR on individual surfaces. The effect of chosen acquisition technique on the full outcrop and the efficacy on its virtual form for quantitative structural analysis and prediction beyond single bedding surfaces, however, is less certain. Here, we compare the accuracy of digital virtual outcrop analysis with traditional field data, for structural measurements and along-strike prediction of fold geometry from Stackpole syncline. In this case, the SfM virtual outcrop, derived from UAV imagery, yields better along-strike predictions and a more reliable geological model, in spite of lower accuracy surface reconstructions than LiDAR. This outcome is attributed to greater coverage by UAV and reliable reconstruction of a greater number of bedding planes than terrestrial LiDAR, which suffers from the effects of occlusion. Irrespective of the chosen acquisition technique, we find that workflows must incorporate careful survey planning, data processing and quality checking of derived data if virtual outcrops are to be used for robust structural analysis and along-strike prediction.

Abstract. Virtual outcrop models are increasingly used in geoscience education to supplement field-based learning but their efficacy for teaching key 3D spatial thinking skills has been little tested. With the rapid increase in online digital learning resources and blended learning, most recently because of the global COVID-19 pandemic, understanding the role of virtual field environments in supporting and developing skills conventionally taught through field-based teaching has never been more critical. Here we show the efficacy of virtual outcrop models in improving 3D spatial thinking and provide evidence for positive perceptions amongst participants using virtual outcrops in teaching and learning. Our results show that, in a simple, multiple-choice scenario, participants were more likely to choose the 3D block diagram that best represents the structure when using a virtual outcrop (59 %) compared to more traditional representations, such as a geological map (50 %) or field photograph (40 %). We add depth to these results by capturing the perceptions of a cohort of students, within our full participant set, on the use of virtual outcrops for teaching and learning, after accessing a virtual field site and outcrops which they had previously visited during a day's field teaching. We also asked all participants if and how virtual outcrops could be used effectively for teaching and training, recording 87 % of positive responses. However, only 2 % of participants felt that virtual outcrops could potentially replace in-field teaching. We note that these positive findings signal significant potential for the effective use of virtual outcrops in a blended learning environment and for breaking barriers to increase the equality, diversity and inclusivity of geoscience field skills and teaching.

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Where primary porosity and permeability of a rock are unfavourable for hydrocarbon production, fractures can improve reservoir potential by enhancing permeability. Higher fracture intensity may create a better-connected fracture network, improving fractured-reservoir quality. Investigations into the controls on fracture intensity commonly conclude that either structural or lithological factors have the greatest influence on fracture abundance. We use the Swift Reservoir Anticline in northwestern Montana to investigate how fracture intensity varies throughout the structure and determine that although structural factors do influence fracture intensity, lithology is the main control at outcrop.The Swift Reservoir Anticline exposes bedding surfaces of the Mississippian Castle Reef Formation dolomite. Field data indicates that fracture intensity is highest in the fold forelimb, decreasing into the backlimb except in outcrops of coarse dolomite where fracture intensity is low, regardless of structural position. Field fracture intensity correlates with whole-rock quartz, kaolinite and porosity percentages. We suggest porosity and composition influence bulk-rock mechanical properties, which, in turn, control the fracture intensity at outcrop. Fracture intensity has a stronger relationship with lithological than structural factors, therefore we suggest that the key to predicting fracture intensity in the subsurface here is understanding how lithology varies spatially.

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