bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimization of Perforation Phasing for Improving Uniformity of Perforation Erosion Through Computational Fluid Dynamic Modelling and Downhole Video Imaging
Authors: Yuan L. , Hu S. L. , Mu L. Y. , Wang D. L. , Yang X. T. 
Published: February 2024

Abstract
The limited-entry technology was a key technology in the multistage fracturing of shale oil and gas horizontal wells to help distribute fracture fluid among multiple perforation clusters evenly. However, perforations could be eroded and enlarged because of high-speed and continuous abrasion by the proppants, resulting in unequal inflow and uneven cracks propagation between perforation clusters, which caused low efficiency of the fracture treatment. Considering that the perforation erosion has not been fully understood yet, special attention should be paid to this aspect of research.
In this paper, perforation erosion models were built using computational fluid dynamics (CFD) to simulate the distribution of the flow field when high-speed fracturing fluid with proppants injected perforations. Then, the flow field analysis was conducted to investigate the impact of the perforation phase on erosion and chambering. Finally, pre-fracturing and post-fracturing erosion data were obtained by the downhole video imaging technology, which was employed to validate against simulation results. Based on above technics, the erosional pattern of perforation would be clearly revealed.
The CFD simulation results demonstrated that, perforations were rapidly eroded to droplets (a typical streamline shape) from the initial round shape because of the much higher erosion rate on the upside of the perforation (near toe) than the downside (near heel). The CFD modelling also noted that there was huge difference of erosion rate between perforations at different phases. Perforations at phase 0 degree (high side of the horizontal wellbore) suffered the minimum erosion rate while perforations at phase 180 degree (down side of the horizontal wellbore) got the maximum. As for perforations at phase 90 and 270 degree, their erosion rates were intermediate，and the values were similar. What's more, the above simulation results were verified by the downhole video imaging data. Most post-fracturing perforations look like droplets. The most eroded perforation was near phase 180 degree with an average diameter of 18 mm which was 1.7 times larger than that of perforations near phase 0 degree (11 mm), while post-fracturing perforations at phase 90 and 270 degree were 13.5mm. Therefore, the 180 degree perforation phasing would help to reduce the uneven erosion and to avoid oversized perforations.
It was a novel approach to integrate the CFD modelling and downhole video imaging technology to quantitatively characterize the perforation erosion pattern, which presented a better dynamic understanding of perforation erosion rather than the previous static analysis by field observations or simulations. This approach would help the optimization of perforation designs and the improvement of field fracturing effect.
Managing Australia's Decommissioning Future and Building Regional Capacity
Authors: Norman F. G. 
Published: February 2024

Abstract
This paper provides an overview of the status of the Australian decommissioning industry and discusses actions and activities that are underway to ensure the industry is as prepared as possible for the growing volume of work it will face this decade. The paper also considers how the growing decommissioning workload can be managed across the region to deliver best in class outcomes and predictable outcomes for all involved.
Driven by reservoirs reaching the end of their production life, the age of existing infrastructure and changes to legislation, the volume of decommissioning activity occurring and planned in Australia has increased significantly this decade. This increase in activity has highlighted several gaps in the readiness across industry; operators have been largely focused on new developments and production with decommissioning taking a lower priority, service sector companies have delayed preparing for decommissioning work due to ongoing uncertainty of workload, and regulators had not been exposed to large enough volumes of decommissioning applications for their personnel to be prepared.
Since its establishment in 2020, the Centre of Decommissioning Australia (CODA) has been working to bring a greater focus on the opportunities and challenges facing industry as decommissioning becomes more common place. This has included CODA's initial work highlighting and quantifying the anticipated volumes and timeline of decommissioning works in Australia. Alongside producing the 2020 forward lookahead, CODA has also been developing reports, resources and tools to help Australian industry prepare for the US$40.5 billion of forecast decommissioning activity.
Regionally, decommissioning workloads are also growing. There is an increasing global demand for skills and equipment, and a growing intersection and tension between offshore decommissioning and offshore wind. Pressures are building on the supply chain to service demand for decommissioning services in Australia, in the Asia Pacific region and globally. Now is the time to explore deeper regional cooperation on this critical final phase of the oil and gas production cycle.
Machine Learning Cement Quality Risk Assessment
Authors: Salehabadi M. , Mohamad Yakup M. A. , Chung S. J. , Buang A. , Jaafar I. , Thanoon D. , Patel C. 
Published: February 2024

Abstract
One of the key elements of well abandonment process is the restoration of regional cap rocks, typically achieved by understanding of quality of cement behind casing by means of interpretation of cement bond logs. The main challenges of cement evaluation, however, are the availability of these logs where these are required, the cost of the acquisition of the data, and well accessibility issues which sometimes prevent the acquisition of the data. The intent of the project is to use machine learning technology to provide an assessment of cement quality based on learning datasets as inputs. Presented here is Phase 1 of a longer study as a proof of concept. Relevant data in the form of petrophysical data, geomechanics data and cement job reports were collated, and then machine learning techniques were applied to identify key parameters which may impact prediction of quality of cement, and subsequently algorithms can then be generated.
A Deep-Learning Framework for the Optimization of CO2 Plume Geothermal Power Production - A Pathway to Carbon Net-Zero
Authors: Katterbauer Klemens , Abdulaziz Qasim , Al Shehri Abdallah , Ali Yousef 
Published: February 2024

Abstract
Several businesses have recently developed CO2 plume geothermal technology (CPG). The concept proposes generating geothermal energy using CO2 trapped in salty aquifers. Compared to traditional geothermal concepts, CPG is unique. In this instance, the feedstock makes use of CO2 as a carrier fluid to draw heat from the subterranean reservoir. Furthermore, the system may use a typical sedimentary substrate rather than only shallow natural hydrothermal areas. Finally, CPG may continue to produce energy in low-temperature settings where it is currently not feasible to do so using traditional geothermal methods. For the purpose of maximizing power generation from a CPG system, we introduce a novel deep-learning optimization methodology. The framework employs a modified N-BEATS methodology. The method is built on an interconnected stack of backcast and forecast connections and ensembled feedforward networks. The framework's versatility with regard to numerous input parameters and different forecastable time series is one of its benefits. This is especially crucial for CPG to effectively capture changes in the temporal dynamics and temperature responses across the numerous CO2 injection and production wells. We assessed the framework on a simulated CO2 storage reservoir based in the Taranaki basin in New Zealand. Given the existence of a sizable saline aquifer that may be ideally suited for CO2 storage and CPG energy generation, the Taranaki basin has been extensively explored for CO2 storage. As input to the Neural basis expansion analysis for time series (N-BEATS) framework, we modeled 3.5 years of CO2 generation and injection for geothermal energy production. The network demonstrated high training performance, and the model's effectiveness was assessed based on the ensuing two years' worth of energy output. The global optimization framework is then combined with the deep learning framework to maximize energy production while modifying CO2 injection. A novel approach to improving energy generation from CO2 storage reservoirs, the new deep learning N-BEATS optimization framework for CPG power generation offers a sustainable means to reduce carbon footprint while delivering electricity.
A Novel Approach of Machine Learning Incorporating Physical Knowledge of Hook Load for Early Stuck Detection
Authors: Inoue Tomoya , Nakagawa Yujin , Kaneko Tatsuya , Wada Ryota , Abe Shungo , Yasutake Gota 
Published: February 2024

Abstract
Early detection of stuck pipe events is pivotal due to their role as major causes of non-productive time. Although researchers have adopted data-driven approaches, such as machine learning, challenging issues persist, such as limited datasets, limited stuck pipe events, and various causes of stuck pipe. This study proposes a novel machine learning approach that incorporates physical knowledge, explaining universal facts, to overcome the aforementioned challenges.
This study creates a prediction model that focuses on the hook load to predict occurrences of stuck pipes. To create the model, we adopted a novel idea that incorporates physical knowledge such as torque and drag models. Because the measured hook load contains uncertainties and is affected by operating conditions, the hook load is expressed using physical knowledge with unknown parameters, and the parameters are determined using data science technologies, including machine learning, based on adjacent historical hook load data. The prediction model is created using only the data in the normal conditions, and the model can express the hook load in normal condition. When the measured hook load exceeds that predicted via the model, it can be assumed that a larger a friction (drag) force is exerted, resulting in a high stuck risk. The deviation, calculated from the predicted and measured hook loads, is acquired, and finally, if the deviation exceeds the normal range determined through data science techniques, including machine learning, the risk of blockage is outputted.
This study initially introduces the stuck pipe predictions using both supervised and unsupervised machine learning approaches. Subsequently, we present machine learning integrating physical knowledge and demonstrate early stuck pipe detection using field data containing stuck pipe events. This novel machine learning approach incorporating physical insights may contribute to significant reduction of nonproductive time in drilling operations, potentially preventing well abandonment.
The Study of Supercritical Carbon Dioxide Trapping Behaviour in Carbonate Reservoirs Through Pore-Scale Imaging Analysis
Authors: Foo Y. Y. , Kashim M. Z. , Mazeli A. H. , Tewari R. D. , Menke H. P. , Singh K. 
Published: February 2024

Abstract
Severe climate change has urged the energy industry to revolutionalise the conventional technologies at pace to curb greenhouse gasses emission for more sustainable future. Carbon Dioxide (CO2) storage at subsurface geological formation remains as the most effective technique to store massive quantity of CO2 safely and permanently. Nonetheless, the flow and trapping behaviours of CO2 at supercritical condition within geological formation are very complex, particularly for the carbonate rocks attributed to the wide spectrum of rock fabrics, pore geometries and structures. This study aims to investigate the pore interconnectivity and residual CO2 trapping during the drainage and imbibition processes within porous media through digital rock technology. Native cores from three carbonate fields with different rock characteristics were plugged to obtain representative samples for the pore-scale coreflooding experiments. Brine and supercritical CO2 were injected into core plugs at temperature up to 120 °C and pressure up to 3000 psi. X-ray images of the saturated core plugs were obtained through micro computed tomography (Micro-CT) facilities after injection of 10 pore volume (PV) of CO2 and 5 PV of brine. Porosity, pore interconnectivity, fluid occupancy, saturation profiles and CO2 ganglia size distribution were measured and studied through the pore-scale imaging analysis. The results indicate that the saturation of CO2 after drainage and imbibition are strongly dependent on the local rock heterogeneity, specifically the presence and distribution of micropores within the rocks. All samples evidently show that micropores play critical role in pore interconnectivity. CO2 ganglia in one sample was observed to be well connected initially but fragmented into smaller sizes after brine imbibition and, lastly, there was no CO2 percolation within the pore network if the flow rate was too low. This paper presents a detailed study in investigating the flow and trapping behaviour of CO2 at supercritical state, providing new insights to the important factors which influence the CO2 trapping. Deeper understanding of the flow and trapping mechanisms is essential to formulate an effective CO2 storage development plan, ensuring minimum injectivity and containment risk throughout the storage period.
Drillpipe Conveyed Casing and Cement Evaluation Allows for Acquisition of Critical Measurements in Parallel with Existing Well Operations
Authors: Hawthorn A. , Steinsiek R. , Leslie I. 
Published: February 2024

Abstract
The oil and gas industry is in a state of continually challenging the way to improve the efficiency and safety of well construction activities. An interesting path has been followed in the last 30 years in the development and use of logging while drilling tools. The measurement quality and reliability of these tools for open hole formation evaluation and geosteering has propelled an entire sequence of highly complex and highly deviated wells with enormous improvements in productivity from existing fields. You would be hard pressed to find any wells, particularly in the offshore domain, that do not utilize logging while drilling measurements that were once the province of wireline tools only. This development of technologies and tools has, as stated above, largely focused on open hole and while drilling applications only. The same cannot be said for cased hole evaluation tools in general, and for well integrity tools that measure the condition and properties of the casing and cement.
This paper will demonstrate the development of a new drillpipe conveyed tool that can both measure the casing condition and what is in the annular space behind the casing. We will show examples from around the world of the tools and the large variety of applications and conditions it has been deployed. Being able to run anytime drillpipe is deployed in the well therefore increases the amount of opportunity to get these critical measurements and also to be run in parallel with existing operations throughout the well construction period. As can be imagined this can lead to considerable efficiency gains as the logging does not require a dedicated run. The basic premise of the tool is that a drill collar is fitted with three circumferential pulse echo ultrasonic transducers. This allows for a full azimuthal image of the casing and annular space behind the casing if the tool is rotated, either from a downhole device such as a mud motor, or by surface rotation through the rig rotary table or top drive. The tool can be run in real-time and also in memory mode, in either case data is both processed downhole and the raw waveforms can be recovered from the tool when back on surface. Analysis of the acquired data allows for interpretation of internal caliper, the thickness of the casing, the location of casing collars and an evaluation of the material in the annular space behind the first casing string. The need to provide oriented images means the tool has magnetometers, accelerometers and a basic gyro measurement device that can be used for orientation of downhole devices such as whipstocks or oriented perforations.
Sequestration of CO2 from High CO2 Gas Field via Bicarbonate Solution for Microalgae Cultivation for Sustainable Biofuels
Authors: Shukor M. Syazwan , Onn M. Syazwan , Ghaddaffi M. , Nor M. , Mukhtar Faiz Azizi 
Published: February 2024

Abstract
It is anticipated based on study, that Natural Gas demand will increase by 65 percent by 2040 (IER, 2014). Hence, oil & gas industries are exploring technologies to unlocking the unconventional natural gas fields. Unconventional gas field contains mostly high contaminants such as carbon dioxide of up to 70 % and 30 % of hydrocarbons gas (Pellegrini et al.,2019). These contaminants can be sequestered in depleted offshore gas fields. However, this approach requires high pressure gas compression energy and availability of storage sites.
To resolve this issue, these contaminants can be sequestered as bicarbonate solution through the injection of carbon dioxide (CO2) into artificial seawater. The formed bicarbonate solution can be the feedstocks for the cultivation of microalgae (Ferreira et al., 2019) to produce sustainable biofuels, bioplastics and bio-based superfood. This method not only promote the effort to lower carbon emissions but also providing solution to enhancing the productivity of biomass production and contribute to the energy demand supply in the form of biofuels. Additionally, the sequestration of CO2 in the form of bicarbonates could benefit in terms of carbon tax savings which can benefit in overall techno economics.
It has been demonstrated through lab experimentation that by harnessing the power of photosynthesis from microalgae and integrating with bicarbonate solution, it has the potential to enhance algae growth and fixing more carbon to the algae as biomass. In conclusion, this novel approach can be the key in helping to reduce the amount of CO2 from extracted unconventional gas fields.
Antifoam Testing to Diminish Gas Entrainment in an Oil-Based Heating Medium
Authors: Lehmann Marc , Fisher Nicholas , Gloyn Mark , Brunt Steven , Tyers Sean 
Published: February 2024

Abstract
An oil-based heating medium (HM) system was found to have a high level of nitrogen gas entrained in the fluids due to the surge drum configuration located in-line with the process flow. The HM surge drum acts as an expansion vessel to account for volume changes when heating from ambient temperature to the operating temperature (260°C). The surge drum is pressurized by supplying nitrogen to reduce the vapor pressure and to maintain inert operating conditions, and is the coldest part of the circuit running between 140-160°C. The return flow from process and utility users was found to "waterfall" into the surge drum. Sampling of the heating medium at the suction side of the discharge pumps drawing heat transfer fluid (HTF) from the surge tank, showed that almost 20 vol% of the heating medium, at standard conditions was nitrogen gas. Modelling showed that the extent of nitrogen gas entrainment would be dependent on the fluid level in the surge tank and would likely originate from bubbles in the size range of 600-1200 microns exiting the Expansion Tank. Gas entrainment in the HTF at elevated operational temperatures is a significant concern that can lead to inefficient heating of the HTF and resulting in a loss of heating control to downstream users. A chemical treatment solution, using an PDMS antifoam agent, was explored to mitigate gas entrainment in the HTF. Foam reduction was observed when the HTF was treated with an antifoam in Foam Column tests. However, the PDMS antifoam agent showed no efficacy in reducing gas entrainment in a modified Ross-Miles Test. The contrast in results was attributed to the fact that the antifoam agent was able to rupture films when applied to actual HTF foam films, however when applied to entrained bubbles dispersed in the HTF, there are no films on which the antifoam can act on. It was concluded that mechanical options are far more likely to mitigate gas entrainment.
Near Well Supercritical CO2 Injectivity Study in Depleted Clastic Gas Field in Offshore Malaysia
Authors: Kashim M. Z. , Shah S. S. Md , Arof M. A. M , Harom-Haron Z. , Khairuddin K. , Tewari R. D. 
Published: February 2024

Abstract
PETRONAS is committed to reduce the bulk carbon dioxide (CO2) emission to the atmosphere by re-injecting the produced CO2 from high CO2 gas field to nearby identified storage site. One of the most important components to develop the storage site would be the understanding on the CO2 injectivity potential. Limited study is identified for near well CO2 injectivity research especially in determining the critical velocity rate to identify the injectivity potential during supercritical CO2 injection (scCO2). In this paper, the injection potential for Field D, which is in Offshore Malaysia has been studies for the storage prospect maturation purposes. Two representative sandstone samples with two distinctive permeability (~80 mD and ~300 mD) from the targeted injected zone in Field D were selected for the analysis. The initially brine saturated core sample was injected with scCO2 at fixed flowrate to establish the core at irreducible brine saturation. ScCO2 was then injected at slightly higher flowrate until the stable differential pressure is achieved. For each subsequent increases in flow rate, base rate of scCO2 is implied in the intervals to observe if there is any formation damage occurred in laminar flow regime. Relative Injectivity Coefficient (RIC) was also calculated using the returned rate differential pressure information. Furthermore, pre- and post-injection core characterization, using routine core analysis (RCA) and X-Ray CT-scan were conducted to examine any petrophysical alteration that might take place during the experiment. The critical velocity rate is then analyzed according to the differential pressure data which later upscaled to well-scale resolution. Based on the differential pressure trend from the two injectivity experiments, there is no clear evidence of formation damage even after the core has been subjected to high scCO2 lab flowrate (~110 cc/min). Only minor dissolution and fines flush-out was occurred. This observation is confirmed by pre- and post-scCO2 injectivity analyses comparison where the petrophysical changes is very minimal. Based on the evidence from differential pressure and pre- and post-sample characteristics, it can be concluded that the critical flow rates were higher than the maximum achievable laboratory flow rates. This denotes that there is no injectivity issues that is expected to occur up to upscaled well flowrate of 18.5 MMscf/day during the CO2 injection in storage target zone in Field D.