Multilayer Technique Research Articles

Best Practices for Database Security in the Age of AI

Database security has seen a dramatic change as a result of artificial intelligence's incorporation into contemporary technology, bringing with it previously unheard-of opportunities as well as obstacles. This thorough article looks at how businesses can use AI capabilities to safeguard sensitive data assets while fortifying their database security postures. With an emphasis on financial institutions and healthcare organizations, it looks at the changing threat landscape, crucial security measures, and practical implementation tactics across a range of sectors. The article further demonstrates the efficacy of threat detection systems, sophisticated encryption techniques, AI-powered security solutions, and thorough audit frameworks. It illustrates the vital significance of putting in place multi-layered security techniques that combine conventional safeguards with AI-enhanced protective measures through in-depth case studies and empirical analysis.

Static pinning synchronization control of self-triggered coupling dynamical networks

In this paper, a new static pinning intermittent control based on resource awareness triggering is proposed. A multi-layer control technique is used to synchronize the coupled neural network. First, a hierarchical network structure including pinned and interaction layers is induced using each pinning strategy. Second, using the ideas of average aperiodic intermittent control (AIC) rate method and constructing an auxiliary function, a new lemma is proposed for the pinning intermittent synchronization of coupled networks, where the upper/lower bound restrictions on each control width for AIC are relaxed. Third, to obtain the desired synchronization behavior, a self-triggering mechanism (STM) is proposed to execute the AIC of the pinned and interaction layers. Moreover, the proposed STM is effective for the actuation of the static pinning impulsive control. The static pinning method modifies the single pinning and switching pinning impulsive control. Finally, the proposed results are applied to Chua’s circuits, oscillators and small-world networks. Experimental results show the performance of the proposed STM which reduces 34.58% the number of control updates compared to a periodically intermittent event-triggered scheme. Further, for large-scale coupled networks, the N-dimensional Laplacian matrix LV can be decomposed into sp×sp and N−sp×N−sp dimensions by hierarchical method, thus reducing the complexity of calculation.

Opportunities with Multi-Layer Weave Structures in Woven E-Textile Design

Most textiles in day-to-day use are products of weaving. The versatility of this manufacturing technique, which readily supports a multi-layered structure, inclusion of several yarn types, malleability and other valuable characteristics, has attracted attention from HCI researchers intrigued by its potential to expand the interaction capabilities of e-textiles. Research nonetheless has barely scratched the surface of the wealth of weaving techniques and woven structures available. Therefore, a design-research project anchored in practice investigated how touch-sensitive e-textiles’ capabilities might be enriched via advanced multi-layer weaving techniques. The research process, which drew inspiration from literature both on textile design and on woven e-textiles, produced 25 distinct e-textile samples. Results from evaluating the structural properties, electrical capabilities and overall utility of each point to numerous unexplored opportunities from woven multi-layer e-textiles. Even holding potential for entirely new forms of interaction, these represent promising starting points for in-depth investigation.

An investigation of past and future LULC using multilayer perceptron-Markov chain techniques: a case study of a Himalayan smart city (2005–2040)

An investigation of past and future LULC using multilayer perceptron-Markov chain techniques: a case study of a Himalayan smart city (2005–2040)

Anterior Skull Base Reconstruction Using a Vascularized Pericranial Flap: A Promising Alternative in Sinonasal Malignancies

Abstract Background As the scope of endoscopic techniques continues to evolve in the treatment of advanced sinonasal malignancies, the primary challenge is the reconstruction of the resulting anterior skull base dural defect. Objective This study aimed to assess the efficacy of vascularized pericranial flap reconstruction in addressing anterior skull base defects in sinonasal malignancies, particularly when alternative reconstructive methods, such as nasoseptal flaps, are not viable. Methods We conducted a retrospective review of nine patients who underwent endoscopic resection of sinonasal malignancy followed by vascularized pericranial flap. Our analysis aimed to evaluate the surgical methods utilized, identify any complications that occurred, and assess the postoperative results of the patients. Results Excluding the singular instance of tension pneumocephalus that emerged during the immediate postoperative period, necessitating surgical intervention, our clinical experience was devoid of any complications, with a median follow-up duration of 18 months. It is worth noting that no cases of cerebrospinal fluid leaks or meningitis were reported. Moreover, the follow-up check endoscopy verified the successful integration of the flap and its efficacious coverage of the resection site. Conclusion This study underscores the benefits of using vascularized pericranial flaps as an alternative solution for anterior skull base reconstruction in sinonasal malignancies. The availability of the pericranial flap in the local region, along with its robust blood supply, and the positive outcomes observed in this preliminary series collectively indicate its potential as an integral component of multi-layered reconstruction techniques for addressing anterior skull base defects.

Multilayer networks in landscape ecology: a case study to assess changes in aquatic habitat connectivity for flying and non-flying benthic macroinvertebrates in a Danube floodplain

ContextIn efforts to mitigate anthropogenic impacts on floodplain biodiversity, restoration measures that enhance habitat connectivity have been applied. However, these approaches have either neglected the spatial position of water bodies or the dynamic nature of the floodplain ecosystem.ObjectivesThis study focuses on the novel application of the multilayer network framework to assess changes in the aquatic habitat connectivity in floodplains, showcasing its application in the context of aquatic passive dispersal (drift) of two indicator groups of benthic macroinvertebrates (Oligochaetes and Chironomids)MethodsOur case study is located in the Donau-Auen National Park in Austria and follows floodplain restoration measures (side-channel reconnection) applied in the mid-1990s. Multilayer networks were constructed to represent the conditions before, short-term, and long-term after restoration to quantify habitat connectivity across inundation frequencies. Our network analyses involved multilayer correlation, static and dynamic monolayer centralities (centrality profiles), and multilayer centrality assessments. We used a Partial Least Squares Regression analysis as a variable selection tool to identify which centrality measures better explained the variance in α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha$$\\end{document} diversity and Local Contributions to Beta Diversity (LCBD) of benthic macroinvertebrates.ResultsIn the short-term, our connectivity analysis indicated an increase in habitat connectivity. However, centrality profiles, multilayer correlation, and multilayer centrality techniques identified a long-term decrease in connectivity. Multilayer centralities had higher Variable Importance in the Projection scores (VIP) than their monolayer counterpart in explaining variations in α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha$$\\end{document} diversity and LCBD for strict aquatic dispersers. Meanwhile, for flying dispersers, monolayer centralities had the highest VIP scores for explaining α\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\alpha$$\\end{document} diversity.ConclusionsThis study underscores the relevance of integrating dynamic aspects of water-mediated transport beyond traditional pairwise distances. Although in this study we apply this tool by showcasing the aquatic passive dispersal mode, the application of this method can be extended to other dispersal modes and representative abilities for diverse groups of aquatic organisms. The expanding cross-disciplinary applications and open-source tool development for multilayer networks offer practical implications for planning and evaluating management measures.

High performance P300 spellers using GPT2 word prediction with cross-subject training

ABSTRACT Amyotrophic lateral sclerosis (ALS) severely impairs patients’ ability to communicate, often leading to a decline in their quality of life within a few years of diagnosis. The P300 speller brain–computer interface (BCI) offers an alternative communication method by interpreting a subject’s EEG response to flashing characters presented on a grid interface. This paper addresses the common speed limitations encountered in training efficient P300-based multi-subject classifiers by introducing innovative ‘across-subject’ classifiers. We leverage a combination of the second-generation Generative Pre-Trained Transformer (GPT2) and Dijkstra’s algorithm to optimize stimuli and suggest word completion choices based on subjects’ typing history. Additionally, we employ a multi-layered smoothing technique to accommodate out-of-vocabulary (OOV) words. Through extensive simulations employing random sampling of EEG data from multiple subjects, we demonstrate significant speed enhancements in typing passages containing rare and OOV words. These optimizations result in approximately 10 % improvement in character-level typing speed and up to 40 % improvement in multi-word prediction. We demonstrate that augmenting standard row/column highlighting techniques with layered word prediction yields close-to-optimal performance. Furthermore, we explore both ‘within-subject’ and ‘across-subject’ training techniques, showing that speed improvements are consistent across both approaches.

Design and Experimental Validation of an Adaptive Multi-Layer Neural Network Observer-Based Fast Terminal Sliding Mode Control for Quadrotor System

This study considers the numerical design and practical implementation of a new multi-layer neural network observer-based control design technique for unmanned aerial vehicles systems. Initially, an adaptive multi-layer neural network-based Luenberger observer is designed for state estimation by employing a modified back-propagation algorithm. The proposed observer’s adaptive nature aids in mitigating the impact of noise, disturbance, and parameter variations, which are usually not considered by conventional observers. Based on the observed states, a nonlinear dynamic inversion-based fast terminal sliding mode controller is designed to attain the desired attitude and position tracking control. This is done by employing a two-loop control structure. Numerical simulations are conducted to demonstrate the effectiveness of the proposed scheme in the presence of disturbance, parameter uncertainty, and noise. The numerical results are compared with current approaches, demonstrating the superiority of the proposed method. In order to assess the practical effectiveness of the proposed method, hardware-in-loop simulations are conducted by utilizing a Pixhawk 6X flight controller that interfaces with the mission planner software. Finally, experiments are conducted on a real F450 quadrotor in a secured laboratory environment, demonstrating stability and good tracking performance of the proposed MLNN observer-based SMC control scheme.

Prediction of CO2 uptake in bio-waste based porous carbons using model agnostic explainable artificial intelligence

This study introduces comprehensive research on the prediction of the carbon dioxide (CO2) uptake from the biomass-waste derived-porous carbons (BWDPCs), by using scientometrics and model agnostic multi-layered explainable artificial intelligence (XAI) techniques. It aims to identify the main characteristics, and trends that are specific to this domain, and to establish, compare and analyse the four different black box machine learning (ML) models for CO2 uptake prediction. For this study, through model evaluation parameters, and scatter plots, statistical analysis supports the fact that the Extreme Gradient Boosting (XGBoost) model is found to be the best performing model for CO2 uptake prediction with low errors and high coefficient of correlation for both training (MSE: 0.157, RMSE: 0.397, MAE: 0.294, MAPE: 0.112, R2: 0.931) and testing phases (MSE: 0.345, RMSE: 0.588, MAE: 0.461, MAPE: 0.121, R2: 0.860). Now, with the best performing black box ML model as XGBoost model, it serves as the basis for the multi-layered XAI analysis. Using multi-layered XAI techniques to interpret the black box ML model and covert it to a white box model, it makes clearer insights into the significant key features that affect the CO2 uptake both at the global and local level. The study demonstrates that using multi-layered XAI analysis helps in improving the trust of the predictive model and provides a way forward for the application of white box models in CO2 uptake.

Liquid crystal phase behavior of oxalated cellulose nanocrystal and optical films with controllable structural color induced by centripetal force

Cellulose nanocrystal (CNC) is a sustainable bio-nanomaterial. The distinctive left-handed polarization properties render cellulose nanocrystal a promising candidate for optical film. Due to eco-friendliness, reliability, mildness and simplicity, the oxalate hydrolysis method stands out among various preparation methods for CNC. This study delved into the liquid crystal phase behavior of oxalated cellulose nanocrystal derived from pulp, and discovered the influences of CNC concentration and pH on suspension stability and phase transition, and evaluated its optical properties. The results demonstrated that oxalated CNC presented two different liquid crystal phases, the nematic phase and the cholesteric phase. The stability mechanism of CNC suspension and the regulatory principle of the liquid crystal phase transition were revealed. A novel CNC film-forming technology, the multilayer spin-coating technique, was developed for cellulose nanocrystal optical films. Driven by centrifugal force, cellulose nanocrystals were induced to self-assembly and formed the optical film with circular dichroism and structural color. This simple and efficient film-forming technology promised rapid processing (1 h) and controllable film structure and optical properties compared to traditional technologies. This work provided a theoretical understanding and practical prospects for integrating oxalated cellulose nanocrystal into sustainable advanced optical film materials.

A multi-layer nesting and integration approach for predicting groundwater levels in agriculturally intensive areas using data-driven models

Agricultural water demand, groundwater extraction, surface water delivery and climate exhibit complex nonlinear relationships with groundwater storage in agricultural regions. As alternatives to computationally intensive physical models, data-driven machine learning methods are frequently employed as surrogates to capture these complex relationships, owing to their high computational efficiency. Inevitably, reliance on a single machine learning model may lead to underestimation of prediction uncertainty and potentially result in reduced accuracy. This paper presents a multi-layer nesting and integration approach for predicting groundwater levels in agriculturally intensive areas using data-driven models. The key contributions of the research are threefold: 1) the development of a comprehensive input variable selection process considering the lag effects and driving mechanisms of groundwater level variations; 2) the implementation of an optimization-based hyperparameter tuning method to enhance the performance of individual machine learning models; and 3) the establishment of a multi-model integration framework based on a multi-layer nesting technique. This approach combines the outputs of multiple machine learning models to consolidate predictions and expand the hypothesis space. The effectiveness of the proposed framework is demonstrated through case studies in the Huaihe River Basin, a major agricultural region in China. The results show that the multi-layer nesting and integration approach outperforms the use of individual machine learning models, providing more accurate and reliable groundwater level predictions. This framework offers valuable insights for decision-makers and water resource managers, supporting sustainable groundwater management and addressing the challenges faced in agriculturally intensive areas.

Barrier Membrane with Janus Function and Structure for Guided Bone Regeneration.

Guided bone regeneration (GBR) technology has been demonstrated to be an effective method for reconstructing bone defects. A membrane is used to cover the bone defect to stop soft tissue from growing into it. The biosurface design of the barrier membrane is key to the technology. In this work, an asymmetric functional gradient Janus membrane was designed to address the bidirectional environment of the bone and soft tissue during bone reconstruction. The Janus membrane was simply and efficiently prepared by the multilayer self-assembly technique, and it was divided into the polycaprolactone isolation layer (PCL layer, GBR-A) and the nanohydroxyapatite/polycaprolactone/polyethylene glycol osteogenic layer (HAn/PCL/PEG layer, GBR-B). The morphology, composition, roughness, hydrophilicity, biocompatibility, cell attachment, and osteogenic mineralization ability of the double surfaces of the Janus membrane were systematically evaluated. The GBR-A layer was smooth, dense, and hydrophobic, which could inhibit cell adhesion and resist soft tissue invasion. The GBR-B layer was rough, porous, hydrophilic, and bioactive, promoting cell adhesion, proliferation, matrix mineralization, and expression of alkaline phosphatase and RUNX2. In vitro and in vivo results showed that the membrane could bind tightly to bone, maintain long-term space stability, and significantly promote new bone formation. Moreover, the membrane could fix the bone filling material in the defect for a better healing effect. This work presents a straightforward and viable methodology for the fabrication of GBR membranes with Janus-based bioactive surfaces. This work may provide insights for the design of biomaterial surfaces and treatment of bone defects.

A Reliable Closure Technique for Retromastoid Craniotomy to Avoid Cerebrospinal Fluid Leaks and Meningitis

BACKGROUND AND OBJECTIVES: Postoperative cerebrospinal fluid (CSF) leaks and meningitis are well-known risks of retromastoid craniotomy. Use of abdominal fat grafts, collagen allografts, and rigid or semirigid buttresses have demonstrated efficacy in preventing CSF leaks and meningitis in endoscopic endonasal surgery. This study aims to determine the utility of a similar multilayered reconstruction technique for retromastoid craniotomy. METHODS: We retrospectively reviewed 212 consecutive patients who underwent retromastoid craniotomy for tumor removal or microvascular decompression from 2007 to 2022. Scalp incisions were linear or slightly curved, muscle and facia opening was performed sharply avoiding monopolar cautery; craniotomies had a maximum dimension of 3 cm. A primary water-tight dural closure was rarely achieved favoring collagen sponge overlay often augmented with autologous fat. Clinical factors including pathology, mastoid air cell entry, and reconstruction material were analyzed. Outcomes including postoperative CSF leakage and meningitis were assessed. RESULTS: Of 212 patients (mean age 56 ± 16 years; 60% female; 10% with prior surgery), 148 (70%) had tumor resection and 64 (30%) had microvascular decompression. Mastoid air cells were breached in 67%. Collagen sponge dural overlay was used in 201/212 (95%). A fat graft was placed in 116 (55%) cases: 69% with air cell entry, 27% without air cell entry; 158 (75%) patients had their bone flap replaced, 46 (21%) had titanium mesh cranioplasty, 8 (4%) had no bone flap or titanium mesh. There were no CSF leaks or meningitis. One patient had a lumbar drain placement preoperatively, none postoperatively. Median length of stay was 2 days. CONCLUSION: Retromastoid craniotomy multilayered reconstruction with liberal use of collagen sponge and abdominal fat grafts seems to reliably avoid postoperative CSF leaks and meningitis including in the setting of nonwatertight dural closure and mastoid cell entry. Use of shorter incisions, avoidance of monopolar cautery, and a relatively small craniotomy may contribute to the absence of CSF leaks in this series.

A New Ultrasound-Guided, One-Point, Single Interfascial Plane Botulinum Toxin A Injection Technique for the Repair of Ventral Abdominal Wall Hernias Before Surgery: A Case Report.

Patients presenting with large ventral abdominal wall hernias require pretreatment with injection botulinum toxin A before surgery. Currently, multipoint and multilayered botulinum injection techniques are practiced. We are describing a new ultrasound-guided, 1-point, single interfascial plane botulinum toxin A injection technique for the closure of big hernial defects.

A novel mixture rule for multi-layer plates with thermal bending and twisting effects applied to FOCoS devices

A novel approach for reducing the simulation time of highly complex fan-out chip on substrate (FOCoS) structures was developed. Based on the Uflyand-Mindlin plate theory and using the multi-layer plate technique, we have successfully obtained the effective elastic and thermal expansion constants incorporating with the effects of bending and twisting for a two-layer plate structure. The newly developed approach was then applied to simulate, by the finite element method, a variety of cases commonly encountered in practice, such as a slightly asymmetric substrate, an extremely asymmetric rigid structure, and an extremely asymmetric soft structure, with a maximum error of only 3 μm. Remarkably, applying the present mixture rule to simulate the complete FOCoS structure has resulted in an error of only 10 μm with up to 75 % of reduction in the number of mesh elements. The present approach, hence, provides an effective and reliable means for simulating the ever increasingly important FOCoS structures in the rapidly evolving information technology applications.

Morbidity of multimodal treatments including endoscopic surgery for sinonasal malignancies: Results of an international collaborative study on 940 patients (MUSES).

In the management of sinonasal malignancies treatment-induced morbidity and mortality is gaining relevance both for surgical approaches (endoscopic and open resection) and non-surgical therapies. The aim of this multicenter study is to assess complications associated with endoscopic surgery and non-surgical treatments (neoadjuvant and/or adjuvant) for malignant sinonasal tumors. All patients with nasoethmoidal malignancies treated with curative intent with endoscopic or endoscopic-assisted surgery at three referral centers with uniform management policies were included. Neo- and/or adjuvant (chemo)radiotherapy was administered according to histology and pathological report. Demographics, treatment characteristics, and complications related both to the surgical and non-surgical approaches were retrieved. The data were analyzed with univariate and multivariate statistics to assess independent predictors of complications. Nine hundred and forty patients were included, 643 males (68%) and 297 females (32%). A total of 225 complications were identified in 187 patients (19.9%): cerebrospinal fluid (CSF) leak (3.5%), mucocele (2.3%), surgical site bleeding (2.0%), epiphora (2.0%), and radionecrosis (2.0%) were the most common. Treatment-related mortality was 0.4%. Variables independently associated with complications at multivariate analysis were principally dural resection (OR 1.92), cranioendoscopic or multiportal resection (OR 2.93), dural repair with multilayer technique with less than three layers (OR 2.17), and graft different from iliotibial tract (OR 3.29). Our study shows that modern endoscopic treatments and radiotherapy for sinonasal malignancies are associated with limited morbidity and treatment-related mortality. CSF leak and radionecrosis, although rare, remain the most frequent complications and should be further addressed by future research efforts.

Endoscopic Transsphenoidal Drainage for Rathke Cleft Cyst With Sellar Xanthogranuloma - Successful Cyst Drainage and Prevention of Postoperative Cerebrospinal Fluid Leakage: 2-Dimensional Operative Video.

The etiology of sellar xanthogranuloma (SXG) remains unclear,1-5 and the surgical strategy for treating SXG is debatable. In this study, we present the surgical case of a symptomatic SXG associated with Rathke cleft cyst. The intraoperative decision to prevent postoperative cerebrospinal fluid (CSF) leakage and secure the drainage route is discussed. A 72-year-old woman presented with severe headaches, visual loss, and gradual enlargement of a cystic lesion on magnetic resonance imaging. The cyst compressed the chiasm upward. The cyst wall was partially thickened and contained a solid mass that was weakly enhanced after gadolinium administration. The endoscopic transsphenoidal cyst was drained, the solid tumor was partially removed for histological diagnosis, and the wide drainage orifice was secured. Intraoperatively, the cyst wall was widely open, but CSF leaked during manipulation of the solid tumor. The sellar floor was partially reconstructed by a multilayer technique to prevent postoperative CSF leakage. The wide cyst drainage route to the sphenoid sinus was also secured. Histologic diagnosis revealed SXG with ciliated columnar epithelium. No postoperative CSF leakage occurred, and the cyst continued to shrink. The patient's visual acuity improved, and pituitary function was preserved. If a CSF leak is identified intraoperatively in a case of secondary SXG associated with Rathke cleft cyst, a cystic fenestration with partial sellar reconstruction may reduce the likelihood of postoperative CSF leakage and ensure continuous drainage. Institutional Review Board approval was not required; The patient consented to the surgery and the publication of her images and surgical video.

Faktor Penentu Pembayaran Zakat Masyarakat Islam di Negeri Terengganu

The statistics of zakat collection by the Terengganu Islamic Religious and Malay Customs Council (MAIDAM) which is increasing from year to year is a very good development for MAIDAM and the Muslim community of Terengganu. Researchers are interested in identifying the factors that influence the compliance of zakat payment by the Muslim community in Terengganu. Thus, this study aims to (i) identify the relationship between the factors of knowledge, exposure, self-efficacy, attitude, and awareness towards zakat payment and (ii) propose a model related to the relationship between knowledge, exposure, self-efficacy, attitude and understanding towards zakat payment. Using quantitative methods, a set of questionnaires developed based on previous studies were distributed to 384 people in the Terengganu Muslim community using multi-layer area sampling techniques and random sampling. The collected data was analyzed using SPSS Version 22 and Smart-PLS Version 3.2.7 software. The findings found that the factors of knowledge, exposure, self-efficacy, and attitude showed a significant relationship to the payment of zakat, while the factor of understanding did not influence respondents in paying zakat. This finding can help related parties in formulating strategies to increase the amount of zakat collection from the Muslim community in the future. However, the findings of this study are only limited to five determining factors. Hence, future research should expand its scope to encompass additional determining factors for more comprehensive outcomes. Keywords: ; ; ; ;

Valorization of Fruit and Vegetables Industry By-Streams for 3D Printing-A Review.

An energy supply crisis is impacting all the branches, including the agriculture and food industry. The wise and responsible utilization of plant raw materials already cultivated is becoming a must in the country's economy. Not only the waste of the resources included but also the environmental challenge are concerns behind the not exploited food production by-streams and leftovers' valorization. Fruits and vegetables' out of the market quality "beauty" standards are still valuable sources of nutritious compounds. The conversion of raw materials into edible products can be provided by many techniques, with three-dimensional printing being the most individualized one. The main objective of this review was to summarize the existing efforts for the valorization of fruits and vegetable residuals into edible 3D inks and then 3D printed products. The clustering analysis was used for the separation of certain research approaches in fruit and vegetable wastes exploitation for 3D printing inks' formulation. As the multilayer deposit technique is strongly dependent on the printing conditions and 3D ink formulation, therefore the tabularized description was included presenting the nozzle diameter, printing speed and other conditions specified.

A semi-analytical fracture high-conductivity location diagnostic method for vertically fractured wells in multilayered reservoirs: field case study

Deep multilayered reservoirs are usually developed using multilayered fracturing techniques; however, the non-uniform placement of proppant causes uneven distribution of fracture conductivity. This study introduces a semi-analytical well test model for hydraulically fractured wells in multilayered reservoirs, accounting for varying fracture conductivity within the hydraulic fracture. The model is built upon the point source function, boundary element method, Duhamel theorem, and pressure superposition principle. Verification tests are conducted to ensure calculation accuracy. Sensitivity analysis is performed on key parameters, encompassing the transmissibility factor, storativity factor, fracture extension, and fracture conductivity. The findings indicate that 1) Increased heterogeneity among layers correlates with a more pronounced pressure drop; 2) Poorly-propped fracture conductivity influences the duration of bilinear flow, becoming negligible after linear flow; 3) The model’s applicability extends to other multilayered reservoirs (e.g., carbonate reservoirs) with minor adjustments. Lastly, a case study from Xinjiang oilfield is presented to demonstrate that the proposed method can derive reservoir and fracture properties for each layer individually. This study contributes to a deeper understanding of the potential of pressure data in characterizing multilayered reservoirs.