Virtual outcrop models of petroleum reservoir analogues: a review of the current state-of-the-art

Pringle, Jamie K.; Howell, John; Hodgetts, David; Westerman, Anthony Robin; Hodgson, David M.

doi:10.3997/1365-2397.2006005

Cited by 162 publications

(105 citation statements)

References 42 publications

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“…These detailed 3D reconstructions of outcrop geology are applied to a broad range of studies, including sedimentology and stratigraphy (e.g., Hodgetts et al, 2004;Enge et al, 2010;Fabuel-Perez et al, 2010;Eide and Howell, 2014;Rarity et al, 2014;Rittersbacher et al, 2014), reservoir modelling (e.g., Enge et al, 2007;Rotevatn et al, 2009;Buckley et al, 2010), and structural geology (e.g., Seers and Hodgetts, 2014;Bistacchi et al, 2015, among others). Light Detection and Ranging (LiDAR) has been the principal acquisition technique for deriving virtual outcrops in the last decade (e.g., Pringle et al, 2006;Buckley et al, 2008;Jones et al, 2009), though acquiring this type of detailed 3D spatial data requires expensive instrumentation and significant knowledge of processing workflows. The recent availability of ready-to-use small Unmanned Aerial Vehicles (UAVs) and the advent of Structure from Motion (SfM) i.e.…”

Section: Introductionmentioning

confidence: 99%

LiDAR, UAV or compass-clinometer? Accuracy, coverage and the effects on structural models

Cawood

Bond

Howell

et al. 2017

Journal of Structural Geology

181

120

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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.

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Section: Introductionmentioning

confidence: 99%

LiDAR, UAV or compass-clinometer? Accuracy, coverage and the effects on structural models

Cawood

Bond

Howell

et al. 2017

Journal of Structural Geology

181

120

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show abstract

“…Depositional architectures are well preserved in outcrops and outcrop analogues offer the opportunity to enhance the understanding of subsurface reservoir architecture, geometry, and facies distributions (Pringle et al, 2006). Compared to studies of modern sedimentary events or laboratory-based experiments and process-based modeling, outcrops are more geologically comparable to the subsurface reservoir architecture and capture large enough scale of heterogeneity.…”

Section: Outcrop Study With Application Of Digital Data Capture Technmentioning

confidence: 99%

Advances and Challenges of Reservoir Characterization: A Review of the Current State-of-the-Art

Jia¹,

He²,

Cai³

2012

Earth Sciences

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“…The dataset used in this study consist of two heli-lidar models (Buckley et al, 2008a;Rittersbacher et al, 2013) and one terrestrial lidar model (Bellian et al, 2005;Pringle et al, 2006). The helicopter-derived data was acquired using the Helimap System (Vallet and Skaloud, 2004;Buckley et al, 2008a); while the terrestrial data were collected using a Riegl Z420i laser scanner with a mounted Nikon D200 digital camera, as described by .…”

Section: Dataset and Methodsmentioning

confidence: 99%

“…The detailed workflow of collecting and processing lidar data captured obliquely from a helicopter is described by Buckley et al (2008a) and Rittersbacher et al (2013), while processing and visualization of lidar data in general are described by Bellian et al (2005), Pringle et al (2006), Enge et al (2007) and Buckley et al (2008b). A brief summary is given below.…”

Section: Lidar Data Collection and Processingmentioning

confidence: 99%

Distribution of discontinuous mudstone beds within wave-dominated shallow-marine deposits: Star Point Sandstone and Blackhawk Formation, Eastern Utah, USA

Eide¹,

Howell²,

Buckley³

2017

Preprint

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Deposits of wave-dominated shorelines are typically considered to act as relatively simple hydrocarbon reservoirs and are commonly modeled as "tanks of sand". However, important heterogeneities that can act as barriers to fluid flow occur at the parasequence, bedset and bed scales, especially in viscous oil or low permeability oil fields. Heterogeneities at the parasequence and bedset scale have been well-studied, but discontinuous mudstone-beds occurring within the shoreface have received little attention.The Book Cliffs and Wasatch Plateau are among the best exposed and most well-studied deposits of wave-dominated shallow-marine systems in the world. Two parasequences within these outcrops have been studied in detail to investigate the distributions of intrashoreface shales and to propose models for the controls on their distribution. A dataset consisting of 30 km of virtual outcrops derived from oblique helicopter-mounted lidar scanning with supporting stratigraphic sections makes it possible to collect a large quantity of accurate geometric data of depositional elements from inaccessible cliffs.A total of 921 discontinuous mudstone beds were measured. These occur as ellipses with long axes oriented normal to the paleoshoreline. Lengths and widths of these mudstone beds exhibit a lognormal distribution, with means of 21.9 and 13.8 m respectively. Within the shoreface succession, the number of mudstone beds increases downwards while size does not vary significantly with stratigraphic height. There is an average of 100 m cumulative length of shale per 100m of horizontal outcrop; this increases threefold near both wave-dominated deltas and bedset boundaries that reflect minor sea-level fluctuations during progradation.

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Virtual outcrop models of petroleum reservoir analogues: a review of the current state-of-the-art

Cited by 162 publications

References 42 publications

LiDAR, UAV or compass-clinometer? Accuracy, coverage and the effects on structural models

LiDAR, UAV or compass-clinometer? Accuracy, coverage and the effects on structural models

Advances and Challenges of Reservoir Characterization: A Review of the Current State-of-the-Art

Distribution of discontinuous mudstone beds within wave-dominated shallow-marine deposits: Star Point Sandstone and Blackhawk Formation, Eastern Utah, USA

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