Doctoral Theses (Energy, Geoscience, Infrastructure and Society)
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Item Marine mammals in the Anthropocene : informing management, planning and conservation(Heriot-Watt University, 2025-04) Hague, Emily Lois; McWhinnie, Assistant Professor LaurenAnthropogenic activities are ubiquitous in the world’s oceans. Understanding the scale and occurrence of threats, and their associated impact(s), is challenging, given many threats are mobile (e.g. maritime vessels), have a heterogenous distribution, and marine species differ in their vulnerability to each particular threat and stressor. Further, marine species, such as marine mammals, are often mobile and inherently cryptic, with heterogenous abundance across their range. The inherent challenges related to studying marine mammals and their threats has limited our understanding of anthropogenic threats to whales, dolphins and seals, and may ultimately result in conservation and mitigation efforts being insufficient or inappropriate. To contribute new understanding on this topic, this first chapter of this thesis develops an evidence base, via a systematic mapping process, to collate currently available knowledge relating to how anthropogenic threats affect nineteen marine mammal species. The resulting outputs highlight a disparity in the volume of records between species, geographic areas, and threats. The potential reasons and implications of such heterogeneity are discussed, and recommendations are provided for filling such gaps. The next chapter evaluated how multiple stressors to marine mammals are considered within the UK’s environmental assessment process. Many maritime industries (such as harbour or renewable energy developments) are legally required to conduct cumulative effects assessments (CEAs) in order to gain consent to carry out certain potentially impactful activities. However, comparison of CEAs found disparity in practice between sectors, despite them occupying broadly the same ocean space and potentially impacting the same marine mammal species. Again, I provide recommendations that will help to standardise practice when it comes to predicting cumulative impacts to marine mammals. Vessels are evidenced to pose multiple potential risks to marine megafauna, including underwater noise, disturbance and fatal or injurious collision. However, the data available to understand this risk is limited. Lack of data can preclude threats from being sufficiently considered within risk or impact assessments and consequently, management efforts. To this end, the remainder of this thesis focuses on exploring approaches to capture data on vessel presence and movement, to later allow for a more holistic evaluation of the occurrence of vessels, and the associated threat this poses to the marine environment. In these chapters, I explore whether the most commonly used vessel data (automatic identification system (AIS)) is reflective of real-world traffic, and thus sufficient for assessment and monitoring. Data gathered between 2019 and 2024 by trained volunteers under the ‘Scottish Vessel Project’ show that AIS data only represented 43% of vessel traffic in coastal areas, 41% of vessel traffic co-occurring with marine mammals, and 36% of vessel traffic in Marine Protected Areas. This new understanding of the volume and occurrence of all vessel traffic can support the more robust quantification of threats associated with vessels in Scotland’s coastal seas, including strike risk, disturbance and noise exposure. Together, this thesis identifies a number of knowledge gaps with regard to our current understanding of threats posed to marine mammals and the wider marine environment, particularly with in regard to evidence of threats from anthropogenic activities (Chapter 2), the way threats to marine mammals are considered by impactful maritime sectors (Chapter 3), and the data available to characterise threats (Chapters 4-6). Throughout, tailored recommendations are provided to address the evidence gaps identified, which, if implemented, could ultimately support the development of more effective threat mitigation measures.Item Accelerating offshore wind development in Indonesia : a case study of South Sulawesi(Heriot-Watt University, 2025-03) Susilawati, Dyah Ika; Porter, Professor Joanne S.; Fruh, Doctor Wolf-Gerrit; Hull, Doctor MarkAbstract and full text unavailable. Restricted access until 29.11.2027. Please refer to PDF.Item A roadmap to enhanced sustainability value in built environment : an optimised impact-framework(Heriot-Watt University, 2025-03) Alkawadri, Dima; Nielson, Doctor Yasemin; Erdogan, Doctor BilgeConstruction and building operations account for a high percentage of Carbon Dioxide (Co2) emissions, according to a United Nations (UN) report 2020 Buildings- Global Status Report (GSR), by the Global Alliance for Buildings and Construction. Emis sions from the construction industry reached the highest ever level in 2019, jeopardising global goals. In 2022, the UN 2022 report shows that construction activities in most major economies have returned to pre-pandemic levels. In addition to environmental concerns, the construction industry has also been found to have a negative impact on socio-economic dimensions. This realisation emphasises the need for significant changes within the sector at various levels to align with sustainability global goals and address these challenges effectively. By the 1990’s, various sustainability initiatives, standards, and certification have been deployed worldwide to reduce the construction industry’s high environmental negative impact. However, studies showed that sustainability initiatives such as Leadership in Energy and Environmental Design (LEED) in the United State of America (USA) have largely failed to realise their intended sustainability benefits in environmental, economic and social dimensions, yet to truly reduce the impact of the construction industry due to several factors. A crucial factor contributing to this shortfall is the decision-making practices of consultants during the project’s inception, particularly in the selection of sustainability credits. This deficiency frequently arises from an absence of a well-defined vision for the project’s intended impact, situated within a broader sustainability strategy. Furthermore, recent studies have highlighted critical knowledge and understanding gaps, pinpointing areas such as the impact of green building decisions on business value, the lack of data to accurately estimate the costs associated with specific sustainability credits, insufficient governance and leadership regarding incentive structures, and an often overlooked consideration of end-user preferences. In previous studies, various decision support methods have been proposed to assist sustainability consultants in the credit selection process. These approaches primarily focused on Green Building Rating Systems (GBRSs) or applied different decision sup port learning techniques. However, these methodologies often prioritise the achievement of specific accreditation levels and scores, neglecting the broader impact of the project from construction through to operation on all stakeholders involved. For frameworks such as LEED to truly succeed, they require benchmark datasets that align closely with each sustainability goal. Shifting the focus towards realising the intended sustainability impact- rather than merely aiming for a certain certification level at a minimal cost can significantly enhance outcomes across environmental, social and economic dimensions. Implementing this approach guarantees that the sustainability strategic goals and objectives of the client organisation are met and simultaneously addresses both environmental objectives and the preferences and needs of the end-user. This research emphasises the crucial necessity to equip sustainability consultants with the tools to make informed decisions that prioritise impactful sustainable solutions, rather than simply targeting high accreditation scores and levels. The research introduces an optimised framework for sustainable developments that constructs a decision-making matrix focused on achieving desired impacts, showcasing Net-Zero as an example theme. This framework integrates standards such as LEED and the WELL Building Standards. Additionally, the framework aligns with the United Nations Sustainable Development Goals (UNSDGs), striving for equilibrium among the sustainability pillars. For practitioners involved in the credit selection process, the proposed framework offers a roadmap on how to optimise sustainability value by focusing on the impact, while balancing both the business value of stakeholders and the comfort and satisfaction of end-users. Uniquely, this research employs Backcasting as a novel method within the sustainability credit selection framework, forecasting future impacts and then interpret these projections retrospectively to refine credit selection strategies for optimal sustainability results.Item Imaging solutions for 4D quantitative interpretation(Heriot-Watt University, 2022-12) Izadian, Saeed; MacBeth, Professor Colin; Amini, Doctor HamedDuring the production of a geomechanically active reservoir, massive pressure depletion happens giving rise to geomechanical changes which can lead to significant time-lapse signals across the reservoir and its surrounding. Therefore, geomechanical characterisation of the reservoir and monitoring are very important for this type of reservoir. In this thesis, I use pre-stack time-lapse time-shifts observed between 4D seismic surveys for the geomechanical characterisation of the Ekofisk field which is a geomechanically active field in the North Sea. This thesis consists of three parts. Before using pre-stack time-shifts, post-stack time shifts can be a valuable guide toward the geomechanical activities of the reservoir. In the first part, I estimate the post-stack time-shifts using various methods. Then, I evaluate the advantages and disadvantages of each method in terms of their performance in revealing the local time-lapse signals such as time-strains. I have found that all the time-shift methods can successfully measure time-shifts. Among them, NLI is the most outstanding method as it gives smooth time-shifts with relatively good accuracy and the time-strains derived from there are more stable and interpretable. In the second part, I use the reflectivity and velocity models of the Ekofisk field and perform a finite-difference simulation to generate synthetic seismic data, followed by imaging the generated data. Migrating baseline and monitor datasets with baseline velocity model caused considerable mispositioning in the overburden resulting in false amplitude-differences in the overburden. The analysis of the images shows that it is not simply a matter of mispositioning that contaminates the seismic images. A more serious problem caused by migration with an erroneous velocity model is the defocusing of amplitudes. This problem cannot be solved by warping and requires a more sophisticated remedy to correct the monitor’s migration velocity model. In the third part, which is the major development of this thesis I measure the pre-stack time-shifts and design a tomographic approach to utilise them for estimating the time lapse changes. First, I show how to measure the pre-stack time-shifts and discuss the practical aspects of the process. Second, I design a ray-based tomography customised for 4D application in order to utilise the pre-stack time-shifts and invert for velocity changes that cause the time-shifts. Finally, I extend the tomography method into an anisotropic inversion where both the time-lapse velocity changes and the ratio of lateral-to-vertical strains are inverted in a two-step inversion process. The two products of the inversion can be used extensively in the geomechanical model calibration of the reservoirs. Overall, my PhD research has successfully measured the time-lapse velocity changes and the ratio of lateral-to-vertical strains. The anisotropic time-lapse tomography is a new paradigm in the pre-stack time-lapse seismic analysis and will be an integrated part of the geomechanical characterisation of the reservoirs.Item Benthic foraminifera as proxies for reconstructing past seawater oxygenation in the Southeast Pacific(Heriot-Watt University, 2025-02) Garrido, Sebastián; Hoogakker, Doctor BabetteIn the current ocean, deoxygenation significantly threatens marine life and ecosystems, particularly in regions with oxygen depleted zones like the Southeast Pacific (SEP). While the response of benthic foraminifera to low oxygen environments has been studied, it remains poorly understood how effectively they can be used to quantitatively reconstruct past oxygen levels, especially in the dynamic SEP with steep oxygen gradients. This thesis addresses this gap by calibrating and applying two benthic foraminifera-based proxies to reconstruct bottom water dissolved oxygen concentrations (BWDO) quantitatively: (i) the test porosity of epifaunal species, mainly Cibicidoides wuellerstorfi, and (ii) the carbon isotope gradient Δδ13C between epifaunal (C. wuellerstorfi) and infaunal (Globobulimina spp.) species, using specimens from surface sediments along the Chilean and Peruvian coasts. A taxonomic revision of the key species used in the calibrations is presented, refining their identification and enabling accurate proxy calibration. Age evaluation of specimens is applied to ensure that specimens accurately reflect modern conditions. Results indicate that both porosity and Δδ13C are reliable proxies for reconstructing BWDO, each with limitations and strengths. The porosity proxy is reliable for BWDO values less than 100 µmol kg-1, and its accuracy in estimating BWDO depends on the number of specimens analyzed and their standard deviation. The Δδ13C proxy is contingent on the availability of Globobulimina species in the samples. It can be applied in waters deeper than 500 m; in shallower low oxygen settings, denitrification may influence the δ13C values of Globobulimina tests. Both proxies were applied to assess the influence of warmer/cooler climates during the Marine Isotope Stage (MIS) 9 and 13 on deep waters in the SEP. Compared with the Holocene, the results show deoxygenation during the warm interglacial period of the Marine Isotope Stage (MIS) 9 and likely higher oxygen levels during the cooler MIS 13. This research refines the application of benthic foraminifera as paleoxygenation proxies, outlining their advantages and disadvantages. Both proxies offer an insightful tool to understand past deoxygenation and to provide potential analogues for future scenarios in a warming worldItem Deep learning for size-agnostic two-phase flow simulation with realistic pore structures and rock-fluid properties(Heriot-Watt University, 2025-02) Asadolahpour, Seyed Reza; Jiang, Doctor Zeyun; Lewis, Doctor Helen; Buckman, Doctor JamesThe study of pore-scale flow in porous media is essential across numerous fields, including petroleum engineering, environmental science, chemical engineering, and biomedicine. Recently, deep learning techniques have shown significant potential in enhancing pore-scale flow modelling. However, existing research predominantly addresses single-phase flow, and studies focusing on the prediction of two-phase flow fields remain sparse. Current deep learning research in two-phase flow typically involves simplified pore structures, limited training datasets, and fixed rock-fluid and flow parameters. In this work, I develop deep neural networks as data-driven proxy models for generating phase distributions during a two-phase, capillary-dominated drainage process, where a non-wetting phase invades a wetting-phase-saturated porous rock. My approach integrates complex Computerised Tomography (CT) images and incorporates pixel size (i.e., imaging resolution), interfacial tension, contact angle (wettability), and capillary pressure as direct inputs. Leveraging these capabilities, I showcase several real-world applications of the trained models. First, I construct an extensive and diverse dataset by subsampling both synthetic and real rock images. Next, an efficient morphology-based drainage simulator is developed, providing phase distributions for each sub-image. I evaluate various deep learning architectures and analyse their accuracy and adherence to physical principles. A recurrent encoder-decoder model outperforms the commonly used U-Net in capturing phase connectivity, though it exhibits flow-direction bias and high computational demands. I subsequently introduce a hybrid transformer-convolutional neural network that performs drainage based solely on pore size, with phase connectivity enforced as a post-processing step. This approach facilitates inference for images of various sizes and accommodates any fluid inlet-outlet configuration. The trained models exhibit high efficiency and accuracy across unseen and larger sandstone and carbonate images. I further validate the models against data from microfluidic experiments and Lattice-Boltzmann (LBM) simulations, demonstrating similar capillary pressure curves and phase distributions with significantly faster performance. These models can replace slow direct simulations or costly experiments, generate finer pressure steps between existing results, and serve as data validation tools. They deliver results in seconds to minutes with minimal preprocessing across a range of realistic rock types, rock-fluid properties, resolutions, and image sizes. I show that the final deep learning models can integrate with an efficient optimiser to estimate wettability if phase distributions are already available. I apply this inverse-problem technique to determine the average contact angle from an LBM-generated phase distribution image in a core-scale Bentheimer sandstone, where supercritical CO2 displaces brine. This scenario has applications in CO2 sequestration. I find that the model achieves results comparable to the GPU-accelerated LBM method, 5,000 times faster. I then generate phase distributions over 101 pressure steps and build the complete capillary pressure curve in minutes. Through these studies, it becomes clear that the developed models can be seamlessly integrated into downstream workflows to provide further insight into pore-scale flow.Item Management of scallop fisheries to reduce the environmental impact on seabed habitats(Heriot-Watt University, 2025-02) Fenton, Mairi Alice; Kaiser, Professor Michel; Bell, Doctor Michael C.The king scallop (Pecten maximus) fishery in the UK is a significant economic resource, contributing over £50 million annually in first sales. However, the primary harvesting method—scallop dredging—raises major environmental concerns due to its impact on seabed habitats. Current management strategies primarily focus on conserving target species, neglecting broader ecosystem protection. This thesis critically reviews global and UK-specific scallop fisheries management practices, revealing the inadequacies of existing measures in addressing environmental damage. By utilising vessel monitoring system (VMS) data, the spatial distribution and intensity of scallop dredging in the UK Exclusive Economic Zone (EEZ) are mapped, highlighting the most affected habitats. A risk assessment framework is developed to identify and prioritise the management of Vulnerable Marine Ecosystems (VMEs) at greatest risk from dredging, highlighting gaps in Marine Protected Area (MPA) management. The thesis also examines the concept of 'marginal' fishing grounds—areas that offer significant conservation benefits while carrying low economic value—suggesting that their protection could minimise ecological harm with minimal economic impact. In addition to spatial and effort-based management, a gear modification aimed at reducing seabed impact was assessed. The addition of skids onto scallop dredges to reduce seabed contact showed promise, though increased bycatch and undersized scallops indicate further refinement is needed. The research emphasises the need for continuous innovation in fishing gear design as part of a comprehensive management strategy. The thesis concludes with recommendations for a holistic, integrated approach to UK scallop fishery management. Combining spatial, effort-based, and technical interventions, this approach offers a sustainable path forward that balances environmental conservation with the economic viability of the fishery for future generations.Item Characterisation of porosity and permeability in reservoir seals using an experimental and upscaled modelling approach(Heriot-Watt University, 2025-02) Sazali, Wan Muhammad Luqman; Busch, Professor Andreas; Buckman, Doctor Jim; Ma, Associate Professor JingshengCarbon capture, utilisation, and storage (CCUS) provide a safe option to achieve net zero carbon emission in 2050. Captured CO2 is usually stored in a deep geological reservoir formation, overlain by a sealing formation known as caprock. Understanding caprock integrity is important in ensuring safe and long-term CO2 containment and storage. Therefore, this research aims to reduce the uncertainties/risk due to the caprock integrity via comprehensive characterisation analysis. However, since caprock is comprised of micropores and nanopores with very low permeability (less than one microDarcy or 10E-18 m2 ), conventional porosimeter and permeameter are not suitable to determine its porosity and permeability. In addition, coring operation in the caprock section is very difficult and expensive, leading to the limited or unavailability of preserved core samples for laboratory analyses. Hence, data from drill cuttings and well logs are used as alternatives when core samples are limited or unavailable. In this research, caprock core samples, drill cuttings, and well log data were selected from S Field, located in offshore East Malaysia, because it is one of the candidates for a CO2 storage site, with a total of 4 wells, including an appraisal well drilled in 2015. This study is comprised of experimental rock characterisation, analyses of well-log data integrated with lab data, and numerical modelling of advective CO2 transport. The rock characterisation analyses include x-ray diffraction (XRD), x-ray fluorescence (XRF), particle size analysis (PSA), thin section petrography, scanning electron microscopy with energy dispersive x-ray (SEM-EDX), low-pressure N2 (LP-N2) sorption analysis, mercury intrusion capillary pressure (MICP), nuclear magnetic resonance (NMR), unsteady state (USS) pulse decay, and helium pycnometry (HP). In addition, broad ion beam (BIB) and focused ion beam scanning electron microscopy (BIB-SEM) were used for digital core analysis (DCA) of caprock samples. Next, well log data from S Field was analysed and integrated with lab data to generate porosity and permeability trends of the caprock of S Field. The data was also used to calculate capillary entry pressure and CO2 column height as part of the caprock integrity assessment. Finally, we studied advective transport of CO2 in S Field using Peng-Robinson (PR) equations of state (EOS) and multiphase fluid flow method. The caprock of S Field has been identified as siltstones since it is dominated by quartz and silts from mineralogical analyses. The caprock is split into two facies, Seal A and Seal B, with differing percentages of clay minerals (20% and 40%, respectively). Seal A is shallower and lies between 800 and 1400 meters below the seafloor. Seal B, on the other hand, is situated between Seal A and the carbonate reservoir and has a burial depth of around 1400 to 1900 meters. The permeability and porosity values determined in the lab, however, do not differ substantially between the two facies. This could be because Seal B is considerably over-pressured compared to Seal A. This excessive pressure could lead to the preservation of porosity during compaction, consequently resulting in enhanced permeability. This finding is consistent with the time-to-depth conversion from seismic data, which identifies Seal B as being less compacted than Seal A. Based on the data integration of the calculated porosity, permeability, capillary entry pressure, and column height, it can be summarised that the seal layers of S Field can contain injected CO2 as long as the reservoir capacity is not exceeded. This finding is supported by the numerical flow models, which show no leakage across the seal in 10,000 years and contained leaks in 1 million years.Item An experimental and numerical study of the kinetics of barium sulphate in flowing systems(Heriot-Watt University, 2025-02) Rafiee, Hamid; Sorbie, Professor Kenneth Stuart; Mackay, Professor Eric JamesThe formation and deposition of mineral scales, such as barium sulphate (BaSO4) and calcium carbonate (CaCO3), is a common problem in many industrial and life science processes. This is caused by chemical incompatibility due to either the mixing of incompatible aqueous solutions or due to changes of the physical conditions, usually temperature and pressure. Many laboratory studies have been conducted using techniques broadly classified into batch and flowing tests to understand the reaction and mechanisms. In this study, we focused on the dynamic (kinetic) deposition of barium sulphate arising from the mixing of 2 incompatible brines. The mechanism of barium sulphate (barite) deposition is often assumed to be a one-step reaction in which the ions in the bulk fluid directly deposit onto a surface. However, there is strong evidence in the literature that barium sulphate may deposit through an intermediary nanocrystalline phase which we refer to as BaSO4(aq) in this work. This initial nucleation species or nanocrystalline material (BaSO4(aq)) may remain suspended in the aqueous system and hence may be transported through the system before it ultimately deposits on a surface In this work, we have formulated a barite formation/deposition model which includes both of these mechanisms noted above, i.e. (i) barite formation in solution of a nanocrystalline precursor which may be transported and deposited at an interface and (ii) the direct kinetic deposition of barite from the free ions in solution. The kinetic approach is most important in flowing conditions, since the residence time in a given part of the macroscopic system (e.g. in a pipe or duct) may be shorter than the time required to reach the full equilibrium state of the system. A CFD study is carried out by solving the Stokes equations to accurately model the local residence time, species transport, and calculate the hydraulic and mass transfer layers. Geometry alteration due depositing barite is also an important phenomenon to consider and model in a flowing system. This is rarely done in mineral deposit calculations, especially with a full kinetic deposition model, but it is included in our model. The geometry change affects both hydraulic and mass transport layers in the vicinity of the depositing surface and may often change the deposition regime in terms of the balance of dominant mechanism which applies. The effect of geometry change on the local residence time is investigated through performing a ramping up of the flow rate and explicitly deforming the geometry as the deposition occurs. We also performed and report experiments on two levels to gain information on the kinetics. First, we studied the kinetics of incompatible brines using batch tests. Second, we developed a laboratory experimental flow cell that enabled us to (i) use different flow geometries through 3D printing, (ii) visualise the deposition process as it happens, and (iii) understand the rates of the reactions by analysing the effluent from the system. We used three different categories of geometries including a (i) simple flow channel, (ii) simple constrictions with different configurations to enforce different mixing regimes, and (iii) more complicated geometry with different constriction sizes. This allowed us to investigate the hypothesis developed in the modelling work. The visual findings from laboratory experiments show the deposition growth happens in the normal direction of the flow, and as the local residence time reduces, the deposition tends to move further down the line. This is true in all three different geometries investigated, showing the concept of the diffusion penetration length. Our results from the modelling and experimental work, show that in the laminar flow regime, the extent of deposition on a surface is limited by the diffusion penetration length (δ) referred to above. This means that there will be more deposits at lower flow rates, where the diffusion penetration length is larger. In this case, since the diffusion penetration length is relatively larger, the deposition mechanism will be kinetics-limited. As the deposition reduces the flow path cross-section area near the inlet vicinity, the velocity increases. Thus, the hydraulic layer becomes smaller, resulting in a smaller diffusion penetration length, which causes the deposition location to move towards the end of the flow path, where the velocity is still lower. In this case, since the diffusion penetration length is relatively smaller, the deposition process will be more transport-limited. The results of this study have the potential to contribute to the development of more effective strategies for preventing scaling in a wide range of industrial processes.Item 3D and 4D inversion for rock and fluid properties using deep learning(Heriot-Watt University, 2025-04) Lew, Chean Lin; MacBeth, Professor Colin; Elsheikh, Professor Ahmed; Côrte, Doctor GustavoThis thesis focuses on estimating rock and fluid properties from the perspective of 3D and 4D seismic inversion. I developed two techniques that enable seamless integration of 3D and 4D seismic data. The first technique emphasises the estimation of porosity, Vclay, and hydrocarbon saturation directly from 3D seismic data using deep learning. Additionally, I propose an approach to enhance the lateral continuity of these estimated petrophysical properties. The products from this first technique are subsequently integrated into the 4D domain, leading to the development of the second technique that enables the inversion for reservoir pressure and saturation changes from 4D seismic data using deep learning. Both techniques involve the use of synthetic training datasets for network training, where the detailed processes for building realistic training datasets are presented. The first technique was tested across four fields with diverse deposition environments, covering meandering fluvial systems, fluvial estuaries, deepwater settings, and carbonate platforms. The second technique was applied to the meandering fluvial field with available 4D seismic data. This technique successfully distinguishes pressure effects from saturation-related effects in the 4D seismic response. It also highlights the importance of incorporating fluid flow information into the training dataset, enabling the network to capture the relationship between the superimposed effects of dynamic property changes and the corresponding 4D seismic response. Finally, I present a summary of the cost-benefit analysis of these developed techniques, demonstrating their ability to accelerate the inversion process in terms of turnaround time while providing robust solutions when applied to field applications.