Core Acquisition Research Articles

Quantifying brain development in the HEALthy Brain and Child Development (HBCD) Study: The magnetic resonance imaging and spectroscopy protocol

The HEALthy Brain and Child Development (HBCD) Study, a multi-site prospective longitudinal cohort study, will examine human brain, cognitive, behavioral, social, and emotional development beginning prenatally and planned through early childhood. The acquisition of multimodal magnetic resonance-based brain development data is central to the study’s core protocol. However, application of Magnetic Resonance Imaging (MRI) methods in this population is complicated by technical challenges and difficulties of imaging in early life. Overcoming these challenges requires an innovative and harmonized approach, combining age-appropriate acquisition protocols together with specialized pediatric neuroimaging strategies. The HBCD MRI Working Group aimed to establish a core acquisition protocol for all 27 HBCD Study recruitment sites to measure brain structure, function, microstructure, and metabolites. Acquisition parameters of individual modalities have been matched across MRI scanner platforms for harmonized acquisitions and state-of-the-art technologies are employed to enable faster and motion-robust imaging. Here, we provide an overview of the HBCD MRI protocol, including decisions of individual modalities and preliminary data. The result will be an unparalleled resource for examining early neurodevelopment which enables the larger scientific community to assess normative trajectories from birth through childhood and to examine the genetic, biological, and environmental factors that help shape the developing brain.

Design and Implementation of Software-Defined Receiver

Acquisition in software-defined GPS receivers is computationally intensive and time-consuming, especially with the increasing demand for rapid and accurate positioning services driven by globalization and digitization. Software-defined receivers face challenges in satellite signal acquisition, which becomes more demanding with longer signals. This paper aims to enhance the efficiency of GPS signal acquisition, a critical step for determining the code phase of PRN codes and the doppler shift in carrier frequency. Real-time applications encounter issues under dynamic conditions and degraded signals, as conventional computers lack the computational power for the necessary correlation and FFT operations. To address these challenges, a method using GPU acceleration for L1 signal acquisition is proposed. This method combines signal acquisition with GPU parallel computing using the SIMT model. A CPU-GPU platform via CUDA programming allows the CPU to handle data reading and intermediate processing, while the GPU performs the core acquisition algorithm in parallel.

A data-driven distributionally robust optimization approach for the core acquisition problem

Reusing electric vehicles (EV) batteries that reach the end of their useful first life is an environmental and cost-competitive option; however, the process of recycling EV batteries is not yet mature. Due to complex electrochemical reactions and physical conditions, the quality of used EV batteries (cores) is highly uncertain. The remanufacturer needs to make the acquisition decision under quality distributional ambiguity. Perfect quality distribution of cores cannot be known to the remanufacturer in practice. We develop distributionally robust optimization models based on phi-divergence measures and the imprecise Dirichlet model (DRO-IDM) to derive robust decisions. First, we find that the bounds of quality probability intervals are identified solely based on the collected data by introducing the imprecise Dirichlet model. The derived finite-sample boundary can reduce the scope of the uncertainty set and avoid the no-direction search issue. Second, our models can hedge against distributional uncertainty, reduce the probability of a robust solution that deviates from the optimal solution, and correct bias in decision making. Third, we extend the DRO-IDM to develop data-driven models, that can reassess the value of multisource quality information to improve the estimation accuracy of core quality and maximize the remanufacturer’s profit. Our study provides new insights for remanufacturers: the new remanufacturing process proposed in our work can assist remanufacturers in utilizing the values of cores without disassembly; the information-aware algorithm can offer the remanufacturing sector a valuable tool for efficiently filtering out invalid information in optimizing acquisition decisions; this capability empowers decision-makers to leverage multiple sources of information and expedite the process of digital transformation in remanufacturing; our approach can also provide a manner of integrating information fusion and distribution learning into remanufacturing.

Analysis of Domestic Acquisitions and Cross-Border Leveraged Buyouts of Companies

With the development of economy, Chinese companies have started to use M&A to expand their business, and more and more core acquisition funds are investing in LBOs. Meanwhile, the pace of China's economic opening to the outside world is gradually accelerating, and many companies are making cross-border M&A to enter the international market, and leveraged buyout, as a special form of M&A for multinational companies, has also attracted attention and spread widely. This paper first analyzes the basic principles, processes, and characteristics of leveraged buyouts. Based on the current situation in China and combined with specific cases, it points out the necessity and problems of applying leveraged buyouts in China. By analyzing and studying two domestic acquisition cases and two overseas acquisition cases, the paper draws some conclusions. Leveraged buyouts are to some extent applicable to M&A activities of Chinese companies. Despite the challenges they pose, leveraged buyouts will remain an important form of M&A for Chinese firms as long as China continues to improve its legal and financial environment and standardize its operational processes. Through an analysis of China's domestic economic situation and current policies on theories related to cross-border investment in overseas M&A, the advantages and risks of cross-border leveraged buyouts are explored and countermeasures for firms to learn from are proposed.

Optimal Core Acquisition and Remanufacturing Decisions With Discrete Core Quality Grades

The acquisition of used products (cores) is essential for leveraging the advantages of remanufacturing. Due to limited historical information about cores, it is difficult for the remanufacturers to accurately assess the quality of cores before disassembly and inspection. In this article, we investigate the joint acquisition and remanufacturing problem with a discrete empirical distribution. Under both deterministic and stochastic demands, two integer programming models are developed to obtain operational rules for making optimal decisions. Since the discrete empirical distribution is assumed to be the nominal distribution or asymptotic distribution of the true quality, the error caused by the difference between the estimated discrete empirical distribution and the true distribution cannot be neglected. Thus, we evaluate the error using the Phi-divergence measure, and the corresponding effects of this difference on the resultant acquisition and remanufacturing rules are analyzed. Through numerical examples, we observe that optimal acquisition and remanufacturing decisions are negatively affected by the difference between the estimated distribution and the true distribution, even if the estimated distribution can pass a hypothesis test. Furthermore, to overcome suboptimal outcomes, a multisource information fusion approach is proposed, which can utilize quality information collected from multiple sources to make accurate acquisition and remanufacturing decisions.

When core sorting and quality grading is beneficial to remanufacturers: Insights from analytical models

In this paper, we study the core acquisition and remanufacturing problem in which the remanufactured products are produced from acquired cores with uncertain quality condition, and are used to satisfy customer demand. Decision-making models are developed to examine the potential value of core sorting and quality grading in the remanufacturing system: a single-period model with deterministic demand, and a single-period model with stochastic demand (i.e., a newsvendor-type model). In each model, both the sorting strategy and the non-sorting strategy are discussed and compared. Our theoretical and numerical results show that: (1) In the deterministic demand case, core sorting is cost-effective only when the unit sorting cost is below a threshold value and the unit acquisition cost falls into a specific interval. Furthermore, in the case with two quality grades the adoption of sorting strategy with respect to the expected fraction of high-quality cores may be non-monotone: an initial increase in the expected fraction of high-quality cores may motivate a switch to core sorting, however, further increase in the expected fraction may motivate a reverse switch; (2) Similarly, in the stochastic demand case, the sorting strategy also becomes unattractive when the unit sorting cost is sufficiently high. In addition, the value of core sorting will be better off under more fluctuating demand for remanufactured products if the sorting strategy is the dominant strategy. Otherwise, it will be worse off.

Optimal Acquisition and Production Policies for Remanufacturing with Quality Grading

Core acquisition is essential to the success of the remanufacturing business. The value of sorting and grading cores into nominal-quality classes has been certified in industry and academia. In this paper, we investigate how many unsorted cores of uncertain quality should be acquired and how many sorted cores should be remanufactured by a third-party remanufacturer (3PR) before the demand is realized. We first develop analytically tractable solutions to the acquisition and production model under deterministic demand, and then we extend it to the model under the stochastic demand by fully characterizing the structure of the optimal policy. Subsequently, we investigate the impact of core quality fraction uncertainty on the solutions. Finally, numerical analyses are conducted to further verify the proposed models. The results are as follows. First, the optimal quantity of acquisition/production and minimum expected profit increase with an increase in the selling price and decrease with an increase in the uncertainty of demand and acquisition cost. Second, the optimal production quantity does not decrease in acquisition quantity, and the rate of utilization of the recycled parts (the ratio of production quantity to acquisition quantity) increases with a decrease in the acquisition cost. Third, the growth stage is most profitable stage, so the remanufacturers should pay more attention to remanufacturing activities early in the life of products. The proposed models and solutions can not only solve the core acquisition and production problem in remanufacturing, but also solve the combinatorial optimization problem.

Prostate Biopsy: General Consideration and Systematic Biopsy

Korea is rapidly entering into an aging society, and an increasing socioeconomic burden related to prostate cancer is inevitable. Therefore, the need for early detection and accurate diagnosis of prostate cancer is becoming increasingly critical. Ideally, a biopsy should accurately detect cancers using a minimum number of cores. However, as prostate cancer is often indistinguishable on imaging, image-guided targeted biopsies alone are insufficient for diagnosis. After decades of trial and error, the diagnosis of prostate cancer relies heavily on systematic biopsy, which is characterized by random and repetitive core acquisition throughout the gland. This review will provide an overview of the historical aspects of prostate cancer diagnosis. Moreover, the review will also address the general considerations involved in prostate biopsy, and discuss the periprocedural management of the patients.

An operator view on trends in core acquisition

Abstract Core samples from the subsurface can provide unambiguous direct information to guide operator decisions. Core may be acquired with drilling equipment (full-bore core) or by post-drill wireline methods (sidewall core). Both approaches have distinct profiles of cost, risk, sample type and value, and an operator must select the most appropriate to progress business in an informed way. The option to selectively core after drilling and perceptions of lower cost and risk might indicate that sidewall coring will always be the best approach. Recent developments to increase the size and quality of rotary sidewall samples would only add weight to this view. It is not all good news for sidewall core, however. Individual sample size and total volume delivered per run are tiny; weak rock or high overbalance pressure may cause poor recovery and biased datasets; time between drilling and logging allows mud invasion and borehole relaxation, so samples are often broken and pore fluids contaminated. Sidewall sample sets therefore leave a higher degree of uncertainty when compared to full-bore core. It is this operator's view that both approaches have a role to play in reducing subsurface uncertainty, and cost, risk and value should be carefully considered when deciding which to apply.

Using Digital Rock Physics to Evaluate Novel Percussion Core Quality

This paper details a benchmarking and validation workflow using digital rock physics (DRP) to evaluate the effectiveness of various percussion sidewall core (PSWC) acquisition methods. The workflow consists of obtaining digital rock properties and images of reference material to compare with material obtained from laboratory percussion sidewall acquisition, including novel designs. This workflow allows insight into the acquisition processes and potential sources of damage in the PSWC technique, and potentially other rock sampling techniques, and offers an opportunity to evaluate its appropriateness as a subsurface rock sample acquisition method. Sample cubes from six outcrop sandstone formations of known properties were used in the testing program to cover a wide range of particularly low and medium unconfined compressive strengths (UCS). Multiple control rotary plug samples were cut from each sandstone formation. The sample cubes were then used as the parent material in laboratory testing of various designs of PSWC bullets. The PSWC bullets, including novel designs, were shot in simulated downhole environments. Both control rotary plug samples and PSWC test core samples were imaged with high-resolution X-ray micro-computed tomography (micro-CT) at resolutions between 2 and 11 μm, and digital rock analysis was conducted on all samples. Using pre- and post-test images, the damage could be identified, and petrophysical properties, including porosity and permeability, could be determined and directly compared with DRP results from control samples and available routine core analysis (RCA) results. DRP provides unique insight to evaluate and quantify changes (or lack of changes) to the sample material subjected to the PSWC acquisition. Damage encountered in the test samples includes grain crushing and compaction that degrades storage and transport properties and dilatant zones that locally enhance transport properties. The presence, frequency, and distribution of these zones are dependent on experimental parameters. In all cases, undisturbed rock fabric could be identified in each sample, and intact texture was verified by comparison with reference material. A novel and efficient method for acquiring and evaluating subsurface samples was developed and benchmarked. Lab results indicate this method may be equally applicable to low- and mid-range UCS rocks. This approach enables a cost-effective reservoir characterization strategy. By optimizing PSWC bullet design and coupling this with mature, image-based digital rock technology, this work demonstrated that the samples and results obtained by this method are representative and that the controls on storage and transport properties are well understood.

Modeling a remanufacturing reverse logistics planning problem: some insights into disruptive technology adoption

Remanufacturing is the process to restore the functionality of high-value end-of-life (EOL) products, which is considered a substantial link in reverse logistics systems for value recovery. However, due to the uncertainty of the reverse material flow, the planning of a remanufacturing reverse logistics system is complex. Furthermore, the increasing adoption of disruptive technologies in Industry 4.0/5.0, e.g., the Internet of things (IoT), smart robots, cloud-based digital twins, and additive manufacturing, has shown great potential for a smart paradigm transition of remanufacturing reverse logistics operations. In this paper, a new mixed-integer program is modeled for supporting several tactical decisions in remanufacturing reverse logistics, i.e., remanufacturing setups, production planning and inventory levels, core acquisition and transportation, and remanufacturing line balancing and utilization. The model is further extended by incorporating utilization-dependent nonlinear idle time cost constraints and stochastic takt time to accommodate different real-world scenarios. Through a set of numerical experiments, the influences of different demand patterns and idle time constraints are revealed. The potential impacts of disruptive technology adoption in remanufacturing reverse logistics are also discussed from managerial perspectives, which may help remanufacturing companies with a smart and smooth transition in the Industry 4.0/5.0 era.

CLASSIFICATION OF QUANTITATIVE MODEL SCENARIOS IN A CLOSED-LOOP SUPPLY CHAIN USING UNDERLYING FACTORS AND VARIABLES: A RESEARCH REVIEW

In a closed-loop supply chain area, the concept of sustainability is one of the primary factors that motivates companies to survive in a dynamic market. The purpose of this paper is to present a literature review of quantitative models in the remanufacturing process, especially mathematical models such as pricing decisions and cost models, reviewed from various scientific journals. Challenges to meet market demands, to boost efficient operational costs, and to increase profits have made researchers interested in deeply exploring this issue. Studies in the reverse supply chain area ensure that the supply process runs effectively and efficiently, meeting a level that is as good as when implementing the forward supply chain. Coordination and collaboration among companies, core acquisition strategy, model character behavior, and reverse channel structure are some characteristics of the quantitative models within the area of a closed-loop supply chain. Mapping was arranged to identify the involvement of research variables (core acquisition cost and remanufactured product price) and factors that were considered in the mathematical model of core acquisition (quantity and quality). Furthermore, the related literature on the issue was analyzed based on the involvement of the considered variables and factors. Finally, future research opportunities are presented as the result of the conducted literature review in this study.

Application of Digital Core Technology in Wellbore Stability Research

Using core to conduct laboratory experiments is one of the important methods for wellbore stability research. However, as the objects of petroleum exploration gradually shift to areas with complex geological conditions, core acquisition is restricted by many problems, such as irregular shapes of cores obtained, low core acquisition rate, long construction time, and increasing operational cost. In recent years, exploration work in the southwest Tarim Basin has been further strengthened. Due to the complex strata and the frequent occurrence of complex well conditions during the drilling process, the problem of on-site coring has become more prominent, which seriously limits the analysis of rock properties. Therefore, scientific and effective cuttings analysis technology is urgently needed. This paper used digital core CT scanning technology to reconstruct the rock skeleton and its mineral facies using drill cuttings. The digital core was established, and the Poisson’s ratio and elastic modulus were calculated. The wellbore stability was analyzed, and the well sections, which were prone to wellbore instability, were determined. On this basis, KCl-polysulfonate drilling fluid was introduced. The influence of drilling fluid on rock strength was evaluated by digital core technology, and water immersion experiments were introduced to verify the experimental results. The results obtained by digital core CT scanning technology were compared with those obtained by triaxial compression experiments and well-logging data calculation, and the feasibility of digital core technology in the wellbore stability study and drilling fluid evaluation was verified.

Petrophysical modeling in the absence of core data in a small, marginal field in the Mumbai Offshore Basin, India

The best petrophysical models are based on direct measurements from the core. Unfortunately, core is not available in many cases, either for economic, logistical, or historical reasons. In this study, we needed to construct a detailed Field Development Plan (FDP) for the small, marginal B-9 field in the Western Offshore Basin, India, which did not merit core acquisition. The objective is to propose a workflow for building a petrophysical model with limited data sets instead of a typical FDP workflow. After analyzing the assumptions, limitations, and uncertainties involved in the petrophysical model, we used advanced petrophysical logs to reduce uncertainty and create a robust petrophysical model. We carried out a log-based petrophysical study to determine the volume of shale, porosity, saturation, and permeability. The advanced petrophysical logs including spectroscopy, nuclear magnetic resonance (NMR), formation pressures, and well testing data are used to calibrate the petrophysical model. Spectroscopy data are used to calibrate the mineralogical volumes and grain density, whereas the porosity is calibrated from NMR data. We calibrated log-derived permeability results with NMR permeability and mobility from well test data. We used heterogeneous rock analysis on petrophysical outputs to carry out petrophysical rock typing (PRT). This has helped in establishing the porosity-permeability relationship and saturation-height model for each PRT. In the absence of irreducible water saturation ([Formula: see text]) information from the core, NMR-derived [Formula: see text] is calculated and then used to calibrate the saturation model. Log-derived permeability and saturation are estimated, which agrees well with the available testing data. This provided a robust petrophysical model that served as a basis for geologic static and reservoir dynamic models. The gas-down-to and water-up-to methods are used to establish the contacts. The resulting saturation height model agreed well with the saturations derived from the log, which gave us confidence in our dynamic model.

A Novel Multi-Criteria Sorting Model Based on AHP-Entropy Grey Clustering for Dealing with Uncertain Incoming Core Quality in Remanufacturing Systems

Remanufacturing is a key pillar of a circular economy and helps in recovering used products by extending their life cycle via remanufacturing them into new products. A vital aspect in a remanufacturing system is the quality assessment of incoming worn-out products (cores) prior to remanufacturing to ensure that non-conforming cores are discarded at an early stage in order to avoid unnecessary processing. Therefore, quality sorting plays an important role in core acquisition for remanufacturing systems when attempting to mitigate uncertain incoming core quality as an immediate solution. The main problem is that it is difficult to acquire the important information required to decide on the sorting of incoming cores, such as the core quality. The data are also commonly limited, not always available, or inaccurate. Grey systems are powerful methods in decision making when handling uncertainty with small data. In this paper, we consider the usefulness of grey systems for handling uncertain quality information for sorting incoming cores in a remanufacturing system. For this reason, we propose a multi-criteria quality sorting model based on an analytical hierarchy process (AHP)-entropy model that is coupled with grey clustering using possibility functions. The quality criteria for sorting the incoming cores are considered according to the technological, physical, and usage conditions. To demonstrate the practical contribution of this research, a case study of the quality sorting problem with a heavy-duty equipment remanufacturer is presented. The proposed model consistently classifies the quality of used hydraulic cylinders into two grey classes.

Linkage Analysis among Factors in Obtaining Return Quantity / Volume: An Interpretive Structural Modelling on Construction Machinery Remanufacturing Industries

Core acquisition management is one of the most crucial activities in remanufacturing industries. The availability of cores is important to support company"s operational functions. This study aims to investigate the supporting factors of a successful core acquisition, focusing on return quantity / volume. Several key factors, considered as the root of the acquisition problem, have been identified through Interpretive Structural Model (ISM) method that involves the opinions of experts. From the initial identification, we obtained nine factors, in which two factors are in the dependent cluster, five factors are in the linkage cluster, and two factors are in the independent cluster. The results of the ISM-based model and MICMAC analysis showed that relationship type (factor 1) and convenience of logistics (factor 4) are the keys to successfully obtain an adequate amount of return quantity / volume. The results showed that the ISM method helps to simplify complex problems and suggest the remanufacturing companies to focus and pay more attention to these two factors, for the success of a core acquisition strategy.

A bi-objective manufacturing/remanufacturing system considering downward substitutions between three markets

An inventory control problem of a hybrid manufacturing/remanufacturing system under stochastic demand is studied. The paper proposes a successive substitution strategy between prime, budget and low budget segments of a market. Meaning a manufactured product may substitute for a remanufactured product at a discounted rate. The success of this proposal proportionally is dependent on the discount rate. Similarly, a once-remanufactured product may substitute for a twice-remanufactured product. In this proposal, a sales-dependent return is adopted to enhance returns prediction. This tactic utilizes a virtual stock of previous period sales instead of a used product stock. In such arrangements, only a fraction of customers accept keeping and returning their used product at the end of the product's lifetime. This is a push system because as soon as the company makes an order for remanufacturing, a core will be returned by a ready/potential customer and instantly will be pushed into the remanufacturing process. The system is formulated by a bi-objective Markov decision process considering profit and customer satisfaction criteria to provide optimal policy in the form of a lookup table. The heuristic policy is then characterized by utilizing five control parameters. This is a state-dependent threshold policy with a small deviation from the optimality. Then the effects of thresholds are investigated applying DOE and ANOVA. Finally, the performance of the successive substitution strategy using real data from the tire industry is examined. The results show that profitability, serviceability and core acquisition can be improved by using the proposed strategy.

Role of remanufacturing in product development and related profit estimation

Companies are preferring a sustainable production system that meets the rigorous environmental regulations and fulfills the demands of customers with a qualitative product. The design for remanufacturing (DfRem) is one favorable strategy that facilitates protecting the latent energy and power in salvaged products/components. This paper presents a mathematical model, which describes DfRem as an integral process in developing a new product under three different scenarios as: i) when only new components are used, ii) when a mix of old and new spare part is used, and iii) when only old components are considered. The paper defines a strategy in choosing the core acquisition mathematically that follows an exponential or delayed S-shaped distribution along with the cost model formulations. Using the non-linear optimization modeling, the proposed framework has been validated on the sales data related to products which belong to altered industries such as automobile, telecommunication, and electronics. Results have shown that a product developed using the combination of old and new components is better as compared to using all new components or all old components. Sensitivity analysis has been carried out to examine the impact of the various parameters on the decision variables. The significance of this study is to provide a solution of procuring components in different manners and producing remanufacturable products using either new or used (old) components to the manufacturers.

Prerequisite factors for original equipment manufacturer remanufacturing

Natural resources are being depleted at an alarming rate, also resulting in increased emissions and pollution. The call for a circular economy and sustainable strategies is now louder than ever. Remanufacturing can alleviate our environmental impact while still providing opportunities for profitable business. However, there is a need for a framework detailing the necessary steps for a successful remanufacturing start-up. This paper aims to identify the essential and supportive factors an original equipment manufacturer (OEM) must consider when transitioning part of its business to remanufacturing. Such factors could aid both current actors in the industrial setting as well as make way for further investigations and more advanced frameworks from the scientific field. The task is carried out through a novel combination of prior research on production development and remanufacturing, with support from a case study performed at an electrical and electronic equipment (EEE) manufacturer. This paper concludes that the first essential factors to be addressed when switching orientation towards remanufacturing can be contained in four categories: core acquisition and reverse logistics, labor skill and availability, remanufacturing facilities, and remanufacturing process and technology. Secondary supporting factors include design for remanufacturing and information feedback, remanufacturing process improvements, remanufacturing market knowledge, and organization, planning and control.

Generating pseudo-capillary pressure curves from nuclear magnetic resonance (NMR) data: a case study from the Cooper Basin, Australia

This study evaluates the accuracy of generating pseudo-capillary pressure curves from laboratory nuclear magnetic resonance (NMR) analysis and NMR wireline log data by comparing threshold pressures and curve characteristics to rock-derived mercury injection capillary pressure (MICP) analysis. Accurate production of pseudo-capillary pressure curves from NMR data could negate or reduce the need for expensive and rig-time-consuming core acquisition and subsequent MICP analysis. Successful application of this technique will allow production of pseudo-capillary pressure curves for large stratigraphic intervals at a significantly reduced cost and help to better constrain petroleum reserves and improve near field exploration prediction outcomes. The Tindilpie-11 well in the Cooper Basin, Australia, was used as a case study because of extensive existing conventional ore analysis and presence of an NMR wireline log covering the sampled intervals in the Permian-aged Patchawarra Formation. Six core samples underwent MICP and laboratory NMR analyses, with capillary pressure curves generated for each method. Six pseudo-capillary pressure curves were also generated from the NMR wireline log data at the coincident sample depths. The pseudo-capillary pressure curves generated from laboratory NMR data closely resemble the MICP results (mean threshold pressure error of 0.63 MPa absolute [91.4 psi]) and proved the applicability of this approach. The NMR wireline log data used is an average over a ∼1.6 m interval, which has likely led to discrepancies when compared with laboratory NMR pseudo-capillary pressure curves and MICP curves. Nonetheless, this study confirms the applicability of using laboratory NMR data to generate pseudo-capillary pressure curves that resemble MICP results. Continued development of NMR log technology and reduced logging speeds will improve the data resolution and ultimately provide high density NMR data that can be used to create pseudo-capillary pressure curves for large stratigraphic intervals at a significantly reduced cost. KEY POINTS Pseudo-capillary pressure curves derived from NMR data. Reservoir characterisation requiring minimal rock acquisition for ground truthing. Case study on the Patchawarra Formation (Cooper Basin, Australia) using SCAL data.