Search

Over the last decades, many studies highlighted the close relationship between thermal structure, surface processes, and tectonic forces in controlling the deformation of the lithosphere. The contribution of these key factors, however, is not constant in time and may result in a complex deformation history, as already observed in many regions around the globe. In this view, the rheology of the crust is pivotal to leading regional tectonic evolution.Among the factors that may cause remarkable strength and rheological variations in the crust, the presence of fluid phases is undoubtedly one of the most prominent. The mechanisms of rock-fluid interaction are still a debated field of research. However, it has been suggested in many studies that a major effect of fluids is enhanced seismicity of regions where they are present.In this framework, the Val d’Agri represents a perfect example of how crustal evolution can be influenced by several factors interacting with one another. In this region, we analyze the relationships between different mechanisms in the final structural setting of the region, with implications on the natural and induced seismicity. To this aim, we built up a numerical model that integrates the combined effects of rheological stratification of the crust, inherited zones of weakness, variations in the tectonic regime, surface erosion, and fluid presence. Our results show that variation in the strength of the evaporite layer between the carbonate platform and the basement has a profound impact on the tectonic style of the Val d’Agri. The uplifting and subsidence pattern in the region follows stages of slow vertical movements to stages of very fast uplifting and denudation, due to the activation of new tectonic structures where movement is enhanced. This reflects on pressure and temperature variations in time, that follow typical yo-yo patterns observed in several tectonically active regions. The present-day configuration of the VA is also influenced by the erosion rate. More in detail, a comparison between the observed structures in the area and our model’s results with varying erosion rates suggests that the VA has been subjected to medium to fast erosion during its evolutionary history. In addition, our model predicts the presence and orientation of faults where fluid percolation or injection at high pressure can generate clusters of microseismicity.

In recent years, there has been a rapid development of the computer-aided interpretation of seismic data to reduce the otherwise intensive manual labor. A variety of seed detection algorithms for horizon and fault identification are integrated into popular seismic software packages. Recently, there has been an increasing focus on using neural networks for fully automatic fault detection without manually seeding each fault. These networks are usually trained with synthetic fault data sets. These data sets can be used across multiple seismic data sets; however, they are not as accurate as real seismic data, particularly in structurally complex regions associated with several generations of faults. The approach taken here is to combine the accuracy of manual fault identification in certain parts of the data set with a convolutional neural network that can then sweep through the entire data set to identify faults. We have implemented our method using 3D seismic data acquired from the Arabian Basin in Saudi Arabia covering an area of 1051 km2. The network is trained, validated, and tested with samples that included a seismic cube and fault images that are labeled manually corresponding to the seismic cube. The model successfully identifies faults with an accuracy of 96% and an error rate of 0.12 on the training data set. To achieve a robust model, we further enhance the prediction results using postprocessing by linking discontinued segments of the same fault line, thus reducing the number of detected faults. The postprocessing improves the prediction results from the test data set by 77.5%. In addition, we introduce an efficient framework to correlate the predictions and the ground truth by measuring their average distance value. Furthermore, tests using this approach also have been conducted on the F3 Netherlands survey with complex fault geometries and find promising results. As a result, fault detection and diagnosis are achieved efficiently with structures similar to the trained data set.

Multilateral wells promise cost savings to oil and fields as they have the potential to reduce overall drilling distances and minimize the number of slots required for the surface facility managing the well. However, drilling a multilateral well does not always increase the flow rate when compared to two single-horizontal wells due to competition in production inside the mother-bore. Here, a holistic approach is proposed to find the optimum balance between single and multilateral wells in an offshore oil development. In so doing, the integrated approach finds the highest Net Present Value (NPV) configuration of the field considering drilling, subsurface, production and financial analysis. The model employs stochastic perturbation and Markov Chain Monte-Carlo methods to solve the global maximising-NPV problem. In addition, a combination of Mixed-Integer Linear Programming (MILP), an improved Dijkstra algorithm and a Levenberg-Marquardt optimiser is proposed to solve the rate allocation problem. With the outcome from this analysis, the model suggests the optimum development including number of multilateral and single horizontal wells that would result in the highest NPV. The results demonstrate the potential for modelling to find the optimal use of petroleum facilities and to assist with planning and decision making.

Summary Cost and schedule overruns are endemic problems for offshore oil projects. This can be partly attributed to weather delays, resource limitations, and scheduling risks. The problem is further compounded because of the large number of interdependent activities, such as drilling and platform installation, typically involved in the buildup period of oilfield development. As a result, there is a pressing need to find robust project planning and scheduling models that consider these interacting components and associated risks in offshore oil projects. This study considers three techniques to optimize offshore oil project schedules while accounting for the impact of numerous field activities and potential delay factors; these are mixed-integer linear programming (MILP), single-objective genetic algorithms (SOGAs), and nondominated sorting genetic algorithms (NSGA-II). The study compares the performance of each using a model that integrates field planning with scheduling while accounting for weather delays, resource limitations, and simultaneous operations (SIMOPS; i.e., the ability to conduct more than one activity at once). The first two techniques (MILP and SOGA) optimize the oilfield schedule based on a single objective, which is to maximize net present value (NPV) or minimize project time. However, the maximum NPV schedule may result in a longer project time, whereas the shortest project time may result in a lower NPV. Therefore, the third method using NSGA-II finds Pareto-optimal schedules that balance these competing objectives. Four case studies are provided to compare the MILP and SOGA approaches with the suggested multiobjective NSGA-II.

Black holes born in the big bang could transform our view of the universe. Is there one lurking on the fringes of the solar system, asks Stuart Clark

The Kidson Sub-basin which forms the largest tectonic province of the Canning Basin has a high potential for Uranium, sediment-hosted base metals, conventional and unconventional hydrocarbons. The basin has undergone major tectonic events since its formation in the Early Ordovician involving several inversion episodes resulting in extensive exhumation in the basin. The magnitude, timing and distribution of exhumation associated with these inversion episodes are poorly studied due to sparse data in the area. In this study, we integrate recently acquired seismic data with existing well data, combining for the first time thermal and compaction techniques to constrain the magnitude and distribution of exhumation associated with these major inversion episodes. Our results indicate that 300 to 500 m of exhumation occurred during the middle Silurian to Early Devonian inversion episode or Prices Creek Compression, 500 to 750 m of exhumation occurred during the middle Carboniferous inversion episode or Meda Transpression and 800 to 1200 m of exhumation occurred during the Late Triassic to Early Jurassic inversion episode or Fitzroy Transpression. Data from apatite fission-track analysis put temporal constraints on the timing of this exhumation and indicate that cooling from maximum post-depositional temperatures within the Kidson Sub-basin occurred in the Late Triassic to Early Jurassic. This imply that a paleothermal maximum was reached within the Kidson Sub-basin during the Early Triassic extension episode, prior to the Fitzroy Transpression. During this period, we also detect that the sediments were affected by a slight increase in basal heat flow associated with the rifting event. Results illustrate that during each of these inversion events, higher amounts of exhumation affected the Kidson Sub-basin than previously thought. The results from this study also demonstrate two dominant factors controlling the spatial and temporal distribution of exhumation in the Kidson Sub-basin. We suggest that the spatial distribution of exhumation in the sub-basin during each inversion episode was dominantly controlled by variation in rheology (strength) of inherited basement units, whilst the temporal distribution of exhumation was dominantly controlled by variation in the magnitude of compressive stress.

Over the last decade, there has been an irreversible shift from hydrocarbon exploration towards carbon storage, low-carbon energy generation and hydrogen exploration. Whilst basin modelling techniques may be used to predict the migration of hydrocarbons through sedimentary basins on geological timescales, there remains little understanding of how fluids behave at the basin scale on present-day timescales. We apply the Darcy flow equation to present an algorithm to determine the basin-scale mobilities and maximum vertical velocity, $$v_{max}$$ v max , of CO$$_{2}$$ 2 , methane, hydrogen and hydrocarbons with depth for sandstone and carbonate. $$v_{max}$$ v max for CO$$_{2}$$ 2 and methane are on scales of m/year, whilst values for hydrocarbon fluids are an order of magnitude smaller than for other fluids. Our results indicate that the fluid mobility of subsurface CO$$_{2}$$ 2 may be sensitive to surface and near-surface temperature variations. $$v_{max}$$ v max for hydrogen is approximately 2–10 times greater than hydrocarbon fluids, yielding important consequences for the future use of basin modelling software for determining hydrogen migration for exploration and storage.

In the past century, cosmologists have created an epic story of an unimaginably vast cosmos that began billions of years ago in a big bang. But can we be sure they have got it right? Stuart Clark audits our cosmological knowledge, providing an essential overview of what we think we know about the universe's vital statistics– and where there is work still to do

The universe is expanding faster than our models can explain. It might be time for a radical rethink of how the cosmos works, says Stuart Clark

Over the last decade, there has been an irreversible shift from hydrocarbon exploration towards carbon storage, low-carbon energy generation and hydrogen exploration. Whilst basin modelling techniques may be used to predict the migration of hydrocarbons through sedimentary basins on geological timescales, there remains little understanding of how fluids behave at the basin scale on present-day timescales. Maximum vertical fluid velocity, vmax, may be calculated as the product of mobility and buoyancy. We present am algorithm to determine the basin-scale mobilities of CO2 and methane with depth for sandstone and carbonate. CO2 and methane mobility and buoyancy increase by an order of magnitude at gas phase transitions and are significantly greater in sandstone than in carbonate. Critical properties of CO2 cause fluid mobility and buoyancy to be sensitive to changes in surface temperature. vmax for CO2 and methane are on scales of m/year. Our results indicate an optimal depth for CO2 storage of below 0.59 km and 1.24 km when surface temperature > 20oC and 0oC, respectively. vmax for hydrogen is approximately 2-10 times greater than other hydrocarbon fluids and this will have important consequences for the future use of basin modelling software for determining hydrogen migration for exploration and storage.

Histories of large-scale horizontal and vertical lithosphere motion hold important information on mantle convection. Here, we compare continent-scale hiatus maps as a proxy for mantle flow induced dynamic topography and plate motion variations in the Atlantic and Indo-Australian realms since the Upper Jurassic, finding they frequently correlate, except when plate boundary forces may play a significant role. This correlation agrees with descriptions of asthenosphere flow beneath tectonic plates in terms of Poiseuille/Couette flow, as it explicitly relates plate motion changes, induced by evolving basal shear forces, to non-isostatic vertical motion of the lithosphere. Our analysis reveals a timescale, on the order of a geological series, between the occurrence of continent-scale hiatus and plate motion changes. This is consistent with the presence of a weak upper mantle. It also shows a spatial scale for interregional hiatus, on the order of 2000–3000 km in diameter, which can be linked by fluid dynamic analysis to active upper mantle flow regions. Our results suggest future studies should pursue large-scale horizontal and vertical lithosphere motion in combination, to track the expressions of past mantle flow. Such studies would provide powerful constraints for adjoint-based geodynamic inverse models of past mantle convection.

Introduction Standard surgical practice of paediatric soft tissue facial injuries requires general anaesthetic (GA) if treatment with local anaesthetic is not tolerated. However, the Covid-19 pandemic has increased the risk of hospital admission for GA to patients and pre-operative Covid-19 testing can delay surgical treatment. In response, a service was established to facilitate short surgical procedures by the Oral and Maxillofacial surgical (OMFS) team with ketamine sedation (KS) at a tertiary level paediatric emergency department. Evaluation of this service demonstrates that KS is a suitable alternative to GA with reduced waiting times, low complications and equivalent surgical outcomes. Method 20 patients treated under KS from May- September 2020 were identified and compared to a control group of 20 patients treated under GA during the same time period. Data including patient demographics, surgical treatment and the KS/GA procedure was collected from the medical records and was analysed using Microsoft excel. Results The KS patients had shorter waits for treatment with 85% of patients waiting 1 day or less, compared with 55% for the GA group. Using the local KS protocol 1 or 2 doses of ketamine was sufficient in 79% of cases and adverse effects were minimal with 21% of KS patients suffering mild nausea and vomiting. Conclusions KS is an acceptable alternative to GA for the management of paediatric soft tissue injuries. KS reduces inpatient admission for GA which is of increased importance during the Covid-19 pandemic. Other OMFS units would benefit from access to a similar service.

Understanding the kinematic processes around the formation of sedimentary basins is central to quantifying their resource potential. Building accurate kinematic models is a subjective and time-cons...

Exploration geophysics and reservoir production strategies rely on a robust knowledge of reservoir petrophysical properties and their uncertainties. We have developed a new approach that not only q...

Extracting key horizons from seismic images is an important element of the seismic interpretation workflow. Although numerous computer-assisted horizon extraction methods exist, they are typically sensitive to structural and stratigraphic discontinuities. As a result, these computer-assisted methods have difficulties in extracting noncoherent dislocated horizons. We have developed a new data-driven method to correlate, track, and extract horizons from seismic volumes with complex geologic structures. Our method correlates seismic horizons across discontinuities and does not require user input in the form of seed points or prior identification of faults. Furthermore, the method is robust toward amplitude changes along a seismic horizon and does not jump from peak to trough or vice versa. We use a large sliding window and match full-length seismic traces using nonlocal dynamic time warping to extract grids of correlated points for our target horizons. Through computed accuracy measurements, we discard nonaccurate correlations before interpolating complete seismic horizons. Because our method does not require manually picked seed points or prior structural restoration, it does not rely on interpretive experience or geologic knowledge. The proposed method is applied on different real and complex seismic images, with two case examples from the southwestern Barents Sea, and one on the open source Netherlands F3 seismic data.

Background Early Intervention in Psychosis (EIP) services improve health outcomes for young people with psychosis in the medium–long term, but 25% of young people disengage in the first 12 months with costs to their mental health, families, society and the NHS. This study will evaluate the effectiveness, cost-effectiveness and implementation of a team-based motivational Early Youth Engagement (EYE-2) intervention. Method The study design is a cluster randomised controlled trial (RCT) with economic evaluation, comparing the EYE-2 intervention + standardised EIP service to standardised EIP service alone, with randomisation at the team level. A process evaluation will evaluate the delivery of the intervention qualitatively and quantitatively across contexts. The setting is 20 EIP teams in 5 sites: Manchester, South London, East Anglia, Thames Valley and Hampshire. Participants are young people (14–35 years) with first episode psychosis, and EIP staff. The intervention is the team-based motivational engagement (EYE-2) intervention, delivered alongside standardised EIP services, and supported by additional training, website, booklets and social groups. The comparator is the standardised EIP service. Both interventions are delivered by EIP clinicians. The primary outcome is time to disengagement (time in days from date of allocation to care coordinator to date of last contact following refusal to engage with EIP service, or lack of response to EIP contact for a consecutive 3-month period). Secondary outcomes include mental and physical health, deaths, social and occupational function, recovery, satisfaction and service use at 6, 12, 18 and 24 months. A 12-month within-trial economic evaluation will investigate cost-effectiveness from a societal perspective and from an NHS perspective. Discussion The trial will provide the first test of an engagement intervention in standardised care, with the potential for significant impact on the mental health and wellbeing of young people and their families, and economic benefits for services. The intervention will be highly scalable, supported by the toolkit including manuals, commissioning guide, training and resources, adapted to meet the needs of the diverse EIP population, and based on an in-depth process evaluation. Trial registration ISRCTN 51629746 prospectively registered 7th May 2019. Date assigned 10th May 2019.