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Monte Carlo Uncertainty Estimation (MCUE) is an emerging heuristic uncertainty propagation method designed to provide reliable and time/cost efficient estimates of geometrical uncertainties in 3D geological modeling. MCUE is a subtype of Bayesian Monte Carlo method similar to geostatistical simulation. The methods described here rely on disturbance probability distributions that are parameterized to best represent individual input uncertainty. Essentially, disturbance distributions quantify the error about the location (x, y, z) and orientation (dip and azimuth) of observed geological structures. The disturbance distributions are sampled either independently or via a Markov-Chain to produce many plausible alternative datasets. These plausible datasets are then input to a 3D geological modeling engine to build a series of plausible alternative model realizations. Further processing may be applied to the series of plausible models to provide valuable decision aids such as probabilistic models, reliability models, or uncertainty reduction hotspot maps. In this paper, a complete and comprehensive MCUE procedure for common drillhole path and log uncertainty propagation is proposed. Basic concepts of drillhole uncertainty are introduced and are applied to a Markov Chain scheme. Appropriate disturbance distributions for the different parts of the problem and their respective parameterization are discussed. The method proposed is demonstrated on three separate proof of concept case studies of increasing complexity. Results demonstrate that the method is able to propagate path and log uncertainty appropriately. First order interpretation indicates that both path and log uncertainty increase with depth and angle of attack to the geological interfaces. Ignoring drillhole uncertainty was found to be detrimental to the understanding of a modeled area which is most likely due to the over-constraining effect brought by “perfect” drillholes. The third case study (Mansfield) hints that uncertainty is better reduced when drillholes intersect the “triple line” that partitions three distinct lithologies. In cross-sections, triples lines appear as triple points.

Exploration programs involve long, multi-branched decision pathways with many potential outcomes from a single starting point. Critical decisions along this pathway include the choice of the area(s) in which to explore, and the choice to acquire new data sets to assist in exploration. Included in this is a factoring of risks, including the technical risks associated with imperfect data and the value relative to cost of collecting more data. In our experience it is not common practice to explicitly assess and quantify the impact of data on exploration decisions. A better understanding of the opportunity provided by data has the potential to improve the quality and/or ease of decision making. In this study we explore the potential role of data richness mapping as part of a decision making workflow. We outline a method to quantitatively assess data richness following a four level hierarchy, namely presence of data (L1), quality of data (L2) and attributes of data (L3). Measures of these are combined across several data sets to give an overall estimate of data richness (L4). Using this data richness map, along with past exploration records and a prospectivity model, we conduct an illustrative case study for gold exploration in the Bryah Sub-basin (Yerrida Basin) region of Western Australia. The first application is to produce a simple data based classification of regions with different technical risk characteristics. The second application is to combine this with a prospectivity model to better understand exploration potential. The third application uses data richness mapping to understand which data sets are most likely to have an impact on regional exploration. In each case we show how an understanding of data richness can help support exploration decision making.

Major structures considered important for controlling mineralisation in the Halls Creek Orogen, east Kimberley are identified via integrated interpretation of geophysical and geological data combined with geodynamic numerical modelling. In the numerical geodynamic models, the second invariant of strain rate ( e II ) is used to investigate the shearing processes that led to the development of major faults or shear zones and assessing their role as lithospheric-scale conduits and pathways for the movement of magmatic and hydrothermal fluids into the upper crust. The influence of these deep structures interpreted from the geodynamic models is evaluated through structural interpretation of geophysical, remotely-sensed and geological data. When compared to the location of Ni and Au mineral deposits the deep-crustal scale structures delineated in the models and compared to those mapped in the region contain a close spatial relationship with mineral deposits. It is apparent that 1st order crustal-scale structures acted as fluid conduits in the deep crust resulting in the formation of Ni-Cu-PGE deposits and are associated with Au mineralisation. However, 2nd and 3rd order structures manifesting in the upper crust as deformation focused mineralising fluids and magma resulting in the formation of gold deposits. Large-scale structures developed early in the genesis of the Halls Creek Orogen, appear to be long-lived and have been reactivated. These form the margins of Kimberley Craton domains and influence the location of Ni-Cu-PGE mineralisation, whereas the lower-order structures acted as structural traps for the subsequent deposition of Au mineralisation.

Extensional episodes in Precambrian orogens are often difficult to decipher because of subsequent orogenesis and intracontinental reworking. Here, we use geochemical and geochronological constraints of a suite of preserved mafic–ultramafic rocks in the Paleoproterozoic Capricorn Orogen of Western Australia to reveal ophiolites, continental ribbons and aborted rifts. The Capricorn Orogen separates the Archean Yilgarn and Pilbara cratons and includes mafic–ultramafic rocks of the fault-bounded Trillbar Complex and Bryah Sub-basin. The Trillbar Complex is situated within a fault wedge between the Yilgarn Craton and a reworked portion of the craton to the north (Yarlarweelor Gneiss Complex), and has been variously interpreted as an obducted ophiolite, oceanic plateau or continental rift-related magmatic suite. In this study, a new U–Pb zircon age of 2069 ± 9 Ma from the Trillbar Complex indicates that it is at least 40 Myr older than the mafic and ultramafic rocks of the Bryah Sub-basin, with which it has previously been linked. The Trillbar Complex is characterised by E-MORB-like signatures, hydrous crystallization and a lack of crustal contamination, and probably formed in a mid-ocean ridge or, alternatively, an oceanic intraplate setting. Conversely, the 2030–1990 Ma mafic and ultramafic rocks in the Bryah Sub-basin show evidence of crustal contamination and are interpreted to have formed in a continental rift setting. Moreover, there is no evidence for boninites in the Bryah Sub-basin and, therefore, no justification for invoking a fore-arc setting. Thus, these pieces of evidence reveal a different tectonic and geodynamic origin for the Trillbar Complex compared to the Bryah Sub-basin rocks. The tectonic setting for the Trillbar Complex requires oceanic crust to have existed between the Yilgarn Craton and the Yarlarweelor Gneiss Complex. However, almost identical Archean histories of these crustal blocks support a proximal origin for the Yarlarweelor Gneiss Complex and a likely origin as a microcontinental ribbon. Farther east (in present-day coordinates), the Bryah Sub-basin and other sedimentary basins record punctuated rifting that never led to the formation of oceanic crust. Therefore, rigorous evaluation of high quality geochemical data coupled to geochronology from mafic–ultramafic rocks is able to provide valuable constraints on extensional episodes, where other evidence has since been erased from the rock record.

With the increasing size and complexity of geoscientific databases, statistical tools and machine learning algorithms are needed to highlight subtle patterns within dense data clouds and reduce human-related bias in geological mapping. This study presents a new tool that maps structural complexity using circular variance and spherical dispersion in two Archean greenstone belts near Dryden and Timmins in the Superior Province, Ontario. Structural complexity quantitatively highlights areas where structures are folded, juxtaposed, and/or parallel. Bedding measurements and autodetected aeromagnetic lineaments are used as inputs to test if structural complexity can refine or add confidence to existing geological interpretations. Linear, low variance trends frequently delineate the location and extent of deformation zones, which likely reflect parallel transposed fabrics in high strain corridors. Areas of high variance spatially correlate with fold traces. Sharp boundaries between high and low variance anomalies are interpreted as faults and/or shear zones that juxtapose structural blocks. The near continuous and representative nature of autodetected magnetic lineaments was effective in capturing structural complexity at a regional scale; however, spherical dispersion captured the highest resolution of structural complexity at local scales ( μ + 1σ). Additionally, the gold grade of large deposits (> 1 Moz) increases with proximity to high variance anomalies. When paired with expert knowledge, these techniques will increase repeatability in future exploration endeavors, making exploration a more rigorous process with increased confidence.

The interaction of structure development and magmatism in rift-settings provides systemic controls on the emplacement of ore deposits both during rifting and subsequently, and a knowledge of these may help to predict better the likely locations of major deposits. The Paleoproterozoic Bryah Rift Basin includes substantial mafic magmatism and deep-crust penetrating structures and possesses syn-rift volcanogenic massive sulphide (VMS) and later gold mineralisation, providing a good opportunity to study interactions between magmatism, structures, and mineralisation. The volcano-sedimentary Bryah Group was deposited in a continental rift developed within the broader Yerrida Basin on the northern margin of the Yilgarn Craton at ca. 2030 Ma. Multi-scale interpretation and forward modelling of gravity and magnetic data were applied to characterise the magmatic and structural patterns of the Bryah Group, enabling a better understanding of its tectono-magmatic development and controls on VMS and gold mineralisation. The interpretation highlights the bounding extensional faults and the inward-deepening structural pattern of the Bryah Rift Basin that reflects the initial rift geometry. Deep-rooted gravity sources show magmatism focused in the southern-central part of the basin, where mafic rocks' thickness can reach more than 10 km. At shallower levels, the rift magmatism extends in three east to east-northeast trending magmatic corridors with an en-echelon arrangement along the rift, oblique to major structures. These magmatic corridors have an intrinsic relationship with the internal structure of the rift. VMS mineralisation associated with mafic magmatism shows a spatial connection with magmatic corridors and major syn-rift faults, whereas VMS mineralisation associated with felsic volcanic rocks is related with off-axis volcanism and regional pre-rift faults. Later orogenic gold mineralisation is also spatially associated with the borders of the magmatic centres and rift faults, despite occurring ~200 Ma later. These associations suggest that primary rift architecture has substantially focused syn-rift VMS mineralisation and also later gold mineralisation, as a consequence of rheological and compositional contrasts.

A regional tectonic model is presented for the formation and evolution of Paleoproterozoic basins over the northern Yilgarn Craton, integrating new and published regional geological, geochronological, geochemical and geophysical data. The basins formed as a response to both extensional and compressional processes in the early Paleoproterozoic along the craton margin. Early rifting and basin formation coincided with the Ophthalmia Orogeny, the result of the convergence and accretion of the Archean to Proterozoic Glenburgh Terrane with the Pilbara Craton, and led to the formation of the Yerrida Basin at c. 2180 Ma as a single sub-basin containing the Windplain Group. This led to the eventual development of the Bryah and Mooloogool Sub-basins of the Yerrida Basin at c. 2030 Ma, and voluminous extrusion and intrusion of mafic rocks. The depth and nature of the Bryah Sub-basin suggests formation in response to rifting, with its orientation corresponding to the rift axis. Continued rifting along the northern Yilgarn margin resulted in subduction of the Yilgarn Craton beneath the composite Glenburgh–Pilbara craton. Eventual collision was marked by cessation of volcanism and rift-sediment deposition in the Bryah and Mooloogool Sub-basins, the onset of a pro-foreland basin (Padbury Basin) in the west, and approximately NE–SW rifting further east (the Earaheedy Basin), all at c. 2000 Ma. Banded iron-formation and granular iron-formation (Robinson Range and Frere Formations) was deposited much later (c. 1890 Ma) in a large basin that deepened from east to west, spanning the Earaheedy and Yerrida Basins. The deepest parts of this basin coincide with the Bryah Sub-basin, which was the most rifted portion of the Yilgarn Craton in this region. Deposition in all basins probably ceased with onset of the Capricorn Orogeny at c. 1820 Ma.

Paleoproterozoic orogens record the accretion and collision of older tectonic blocks, and this record the tectonic development of a region. The Halls Creek Orogen (HCO) is a well-exposed Paleoproterozoic orogenic belts which can provide insight into the assembly of the Kimberley Craton to the Diamantina Craton during the Nuna Supercontinent amalgamation. Despite the relative abundance of rock exposure, there is still controversy as to how the Halls Creek Orogen developed. The 1865 Ma Tickalara Metamorphics seem to be a key unit within the Central Zone of the Halls Creek Orogen that can help solving the controversy. The formation of the protoliths to the Tickalara Metamorphics, and other sedimentary and igneous rocks of Central Zone have been described as either forming in: (1) an oceanic island arc setting above an easterly dipping subduction zone outboard of Kimberley Craton; or (2) an ensialic marginal basin located closer to the margin of Kimberley Craton. The two plausible tectonic scenarios of the Halls Creek Orogen are examined through 33 2D thermo-mechanical-petrological numerical experiments based on I2VIS code. The initial constraints for model setup aim to best represent the tectonic environment for the protoliths to the Tickalara Metaomorphics as either intra-ocean subduction or ocean-continent subduction and collision. With this approach, we were able to find experiments with specific physical parameters with results that are consistent with the geology observed in the Halls Creek Orogen. The results indicate that the geology of the Halls Creek Orogen is best represented by the ensialic marginal basin scenario. This scenario is most consistent with the observed geology and reveals processes which led to the generation of key lithological units and major structures. The numerical experiments can also explain sources of magmatism and development of metamorphic conditions that occurred during the tectonic evolution of the Halls Creek Orogen.

Topology has been used to characterise and quantify the properties of complex systems in a diverse range of scientific domains. This study explores the concept and applications of topological analysis in geology. We have developed an automatic system for extracting first order 2D topological information from geological maps, and 3D topological information from models built with the Noddy kinematic modelling system, and equivalent analyses should be possible for other implicit modelling systems. A method is presented for describing the spatial and temporal topology of geological models using a set of adjacency relationships that can be expressed as a topology network, thematic adjacency matrix or hive diagram. We define three types of spatial topology (cellular, structural and lithological) that allow us to analyse different aspects of the geology, and then apply them to investigate the geology of the Hamersley Basin, Western Australia.

Uncertainty is ubiquitous in geology, and efforts to characterise and communicate it are becoming increasingly important. Recent studies have quantified differences between perturbed geological models to gain insight into uncertainty. We build on this approach by quantifying differences in topology, a property that describes geological relationships in a model, introducing the concept of topological uncertainty. Data defining implicit geological models were perturbed to simulate data uncertainties, and the amount of topological variation in the resulting model suite measured to provide probabilistic assessments of specific topological hypotheses, sources of topological uncertainty and the classification of possible model realisations based on their topology. Overall, topology was found to be highly sensitive to small variations in model construction parameters in realistic models, with almost all of the several thousand realisations defining distinct topologies. In particular, uncertainty related to faults and unconformities was found to have profound topological implications. Finally, possible uses of topology as a geodiversity metric and validation filter are discussed, and methods of incorporating topological uncertainty into physical models are suggested.

Predicting realistic targets in underexplored regions proves a challenge for mineral explorers. Knowledge-driven prospectivity techniques assist in target prediction, and can significantly reduce the geographic search space to a few locations. The mineral prospectivity of the underexplored west Kimberley region was investigated following interpretation of regional gravity and magnetic data. Emphasis was placed on identifying geological structures that may have importance for the mineral prospectivity of the region. Subsurface structure was constrained through combined gravity and magnetic modelling along three transects. Crustal-scale structures were interpreted and investigated to determine their depth extent. These interpretations and models were linked to tectonic events and mineralization episodes in order to map the distribution of minerally prospective regions using a knowledge-driven mineral systems approach. A suite of evidence layers was created to represent geological components that led to mineralization, and then applied to each mineral system where appropriate. This approach was taken to provide a more objective basis for prospectivity modelling. The mineral systems considered were 1) magmatic Ni-sulphide, 2) carbonate-hosted base metals, 3) orogenic Au, 4) stratiform-hosted base metals and 5) intrusion-related base metals (including Sn–W, Fe-oxide–Cu–Au and Cu–Au porphyry deposits). These analyses suggest that a geologically complex belt in the Kimberley Basin at the boundary to the King Leopold Orogen is prospective for magmatic-related hydrothermal mineral systems (including Ni, Au and Cu). The Lennard Shelf is prospective for carbonate-hosted base metals around a feature known as the 67-mile high, and parts of the King Leopold Orogen are prospective for stratiform-hosted base metals. These results show that knowledge-driven mineral system modelling is effective in identifying prospectivity in regional-scale studies of underexplored areas, as well as drastically reducing the search space for explorers working in the west Kimberley.

The east Kimberley region contains well-preserved tectonic structure dating back to the Earth’s most significant stage of continental growth: the assembly of the Nuna supercontinent. An integrated geological–geophysical investigation of this region has been conducted and reveals insight into its tectonic evolution, including potential influence of significant crustal-scale structures in the development of regional architecture, the emplacement of magma, and the relationship of these structures to large-scale deformation. Some newly interpreted features include a north-trending structure, and three north-west trending structures that segment the north-east trending orogen. The central segment of the orogen is a zone of higher metamorphic grade, and is host to a distinct gravity high. This gravity high can be explained by excess mass in the mid-crust. This anomaly is consistent with either a large mafic–ultramafic intrusion or a high-density crustal fragment. Possible tectonic models to explain the geophysical and metamorphic anomalies involve, in the latter case, the accretion of a crustal fragment to the Kimberley Craton prior to the 1865–1850 Ma Hooper Orogeny or, in the former case, intrusion of voluminous mafic magmas into the middle crust. Whether by igneous or structural means, we consider the development of this anomalous region to be a result of along-strike variations in subduction dynamics. These were perhaps driven by variations in slab-geometry accommodated by the orogen-normal structures we identify. The orogen-normal structures are interpreted to be crustal-scale faults, along which significant vertical displacement occurred when a crustal fragment collided with Kimberley Craton and exhumed high-grade metamorphic rocks to the surface.

Geological structures are recognisable as discontinuities within magnetic geophysical surveys, typically as linear features. However, their interpretation is a challenging task in a dataset with abundant complex geophysical signatures representing subsurface geology, leading to significant variations in interpretation outcomes amongst, and within, individual interpreters. Previously, numerous computational methods were developed to enhance and delineate lineaments as indicators for geological structures. While these methods provide rapid and objective analysis, selection and geological classification of the detected lineaments for structure mapping is in the hands of interpreters through a time consuming process. This paper presents new ways of assisting magnetic data interpretation, with a specific aim to improve the confidence of structural interpretation through feature evidence provided by automated lineament detection. The proposed methods produce quantitative measures of feature evidence on interpreted structures and interactive visualisation to quickly assess and modify structural mapping. Automated lineament detection algorithms find the feature strengths of ridges, valleys and edges within data by analysing their local frequencies. Ridges and valleys are positive and negative line-like features detected by the phase symmetry algorithm which finds locations where local frequency components are at their extremum, the most symmetric point in their cycle. Edge features are detected by the phase congruency algorithm which finds locations where local frequency components are in phase. Their outputs are used as feature evidence through interactive visualisation to drive data evidenced interpretation.Our experiment uses magnetic data and structural interpretation from the west Kimberley region in northern Western Australia to demonstrate the use of automated analysis outputs to provide: quantitative measures of data evidence on interpreted structures, and graphical evaluation of interpretation quality.

Opening up greenfields regions for mineral exploration programs is facilitated through understanding their mineral prospectivity. The Capricorn Orogen in Western Australia can be considered such a greenfields-dominated region, that hosts several mineral occurrences or deposits, but only a few have been mined extensively. Mineralisation in much of the Capricorn Orogen can be related to basin development, inversion and orogenesis during the Paleoproterozoic. Extension, on a regional scale, dominates the tectonic processes observed in the area through time and is interspersed by periods of contractional orogenesis, including the 2005–1950 Ma Glenburgh and 1830–1780 Ma Capricorn orogenies. Prospectivity models for base metals and gold in the northern and southern parts of the Capricorn Orogen suggest there is a spatial link between potentially prospective zones and the Archean basement, but also between the base metal and gold mineral systems. One of these links is tied to the control of the deep crustal-scale tectonic architecture over basin development and subsequent inversion during orogenesis. This early architecture contributed towards the preservation of mineralisation by protecting the area from tectonothermal processes such as deep burial and metamorphism. In addition, the spatial concurrence of zones prospective for the c. 2 Ga Au-Cu volcanic massive sulphide and c. 1.8 Ga orogenic Au style mineralisation in the northern part of the Bryah Sub-basin suggests a spatial link between the two mineral systems, while supporting the hypothesis that deposition of different ore styles is driven by long-lasting, regional geodynamic processes. In the Capricorn Orogen, these changing conditions reflect the transition from a plate-margin setting to an intraplate setting.

Banded iron formation (BIF) deposits are the most important source of iron in China, and they are dominantly distributed in the North China Craton (NCC). The Anshan-Benxi area is situated in the northeastern part of the NCC and is considered to be the most fertile and productive iron metallogenic province in China. The recent successive discoveries of large BIF deposits in this area, especially the world-class Dataigou BIF deposit, indicates that there is great potential for iron resources in this area. The BIF deposits are well defined by magnetic and gravity anomalies and thereby extensive petrophysical and geophysical studies are critical for BIF prospective mapping. A data-driven weights-of-Evidence (WofE) analysis was used for BIF prospectivity modeling. The results indicated that prospective areas are generally confined to the Precambrian greenstone belt basin and high-prospectivity zones (Class A) are mainly distributed in the middle and northeastern parts of the study area. Moderate-prospectivity zones (Class B) are mainly distributed in southwestern and northeastern parts of the study area. Finally, we employed selective human intervention to redefine priority targets to be more reliable. The results suggest the method is successful as 82 target areas were narrowed to Class A 20 and 11 Class B targets. The total of Class A and Class B targets was just over one-third of the total number of targets, offering a much smaller but effective selection of targets for consideration by mineral explorers.

Mineral exploration programs commonly use a combination of geological, geophysical and remotely sensed data to detect sets of optimal conditions for potential ore deposits. Prospectivity mapping techniques can integrate and analyse these digital geological data sets to produce maps that identify where optimal conditions converge. Three prospectivity mapping techniques – weights of evidence, fuzzy logic and a combination of these two methods – were applied to a 32,000 km 2 study area within the southeastern Arizona porphyry Cu district and then assessed based on their ability to identify new and existing areas of high mineral prospectivity. Validity testing revealed that the fuzzy logic method using membership values based on an exploration model identified known Cu deposits considerably better than those that relied solely on weights of evidence, and slightly better than those that used a combination of weights of evidence and fuzzy logic. This led to the selection of the prospectivity map created using the fuzzy logic method with membership values based on an exploration model. Three case study areas were identified that comprise many critical geological and geophysical characteristics favourable to hosting porphyry Cu mineralisation, but not associated with known mining or exploration activity. Detailed analysis of each case study has been performed to promote these areas as potential targets and to demonstrate the ability of prospectivity modelling techniques as useful tools in mineral exploration programs.

The process of building a 3D model necessitates the reconciliation of field observations, geophysical interpretation, geological data uncertainty and the prevailing tectonic evolution hypotheses and interpretations. Uncertainty is compounded when clustered data points collected at local scales are statistically upscaled to one or two points for use in regional models. Interpretation is required to interpolate between sparse field data points using ambiguous geophysical data in covered terranes. It becomes clear that multiple interpretations are possible during model construction. The various interpretations are considered as potential natural representatives, but pragmatism typically dictates that just a single interpretation is offered by the modelling process. Uncertainties are introduced into the 3D model during construction from a variety of sources and through data set optimisation that produces a single model. Practices such as these are likely to result in a model that does not adequately represent the target geology. A set of geometrical ‘geodiversity’ metrics are used to analyse a 3D model of the Gippsland Basin, southeastern Australia after perturbing geological input data via uncertainty simulation. The resulting sets of perturbed geological observations are used to calculate a suite of geological 3D models that display a range of geological architectures. The concept of biodiversity has been adapted for the geosciences to quantify geometric variability, or geodiversity, between models in order to understand the effect uncertainty has models geometry. Various geometrical relationships (depth, volume, contact surface area, curvature and geological complexity) are used to describe the range of possibilities exhibited throughout the model suite. End-member models geodiversity metrics are classified in a similar manner to taxonomic descriptions. Further analysis of the model suite is performed using principal component analysis (PCA) to determine important geometrical characteristics. The configuration of the model space is determined through identifying ‘outlier’ model examples, which potentially represent undiscovered model ‘species’.

Geological three-dimensional (3D) models are constructed to reliably represent a given geological target. The reliability of a model is heavily dependent on the input data and is sensitive to uncertainty. This study examines the uncertainty introduced by geological orientation data by producing a suite of implicit 3d models generated from orientation measurements subjected to uncertainty simulations. The resulting uncertainty associated with different regions of the geological model can be located, quantified and visualised, providing a useful method to assess model reliability. The method is tested on a natural geological setting in the Gippsland Basin, southeastern Australia, where modelled geological surfaces are assessed for uncertainty. The concept of stratigraphic variability is introduced and analysis of the input data is performed using two uncertainty visualisation methods. Uncertainty visualisation through stratigraphic variability is designed to convey the complex concept of 3D model uncertainty to the geoscientist in an effective manner. Uncertainty analysis determined that additional seismic information provides an effective means of constraining modelled geology and reducing uncertainty in regions proximal to the seismic sections. Improvements to the reliability of high uncertainty regions achieved using information gathered from uncertainty visualisations are quantified in a comparative case study. Uncertainty in specific model locations is identified and attributed to possible disagreements between seismic and isopach data. Further improvements to and additional sources of data for the model are proposed based on this information. Finally, a method of introducing stratigraphic variability values as geological constraints for geophysical inversion is presented.

A 40-year-old man sustained a circumferential crush injury to his right forearm. Four months after injury, he experienced the onset of numbness and tingling in the distribution of the median nerve after exercise. Elevated compartment pressures of the palmar forearm and slowing of median nerve conduction after exercise suggested chronic exertional compartment syndrome. A flexor fasciotomy led to complete relief of symptoms, which allowed the patient unrestricted activity.