Seismic geometric attribute analysis for fracture characterization: New methodologies and applications

In 3D subsurface exploration, detection of faults and fractures from 3D seismic data is vital to robust structural and stratigraphic analysis in the subsurface, and great efforts have been made in the development and application of various seismic attributes (e.g. coherence, semblance, curvature, and flexure). However, the existing algorithms and workflows are not accurate and efficient enough for robust fracture detection, especially in naturally fractured reservoirs with complicated structural geometry and fracture network. My Ph.D. research is proposing the following scopes of work to enhance our capability and to help improve the resolution on fracture characterization and prediction.;For discontinuity attribute, previous methods have difficulty highlighting subtle discontinuities from seismic data in cases where the local amplitude variation is non-zero mean. This study proposes implementing a gray-level transformation and the Canny edge detector for improved imaging of discontinuities. Specifically, the new process transforms seismic signals to be zero mean and helps amplify subtle discontinuities, leading to an enhanced visualization for structural and stratigraphic details. Applications to various 3D seismic datasets demonstrate that the new algorithm is superior to previous discontinuity-detection methods. Integrating both discontinuity magnitude and discontinuity azimuth helps better define channels, faults and fractures, than the traditional similarity, amplitude gradient and semblance attributes.;For flexure attribute, the existing algorithm is computationally intensive and limited by the lateral resolution for steeply-dipping formations. This study proposes a new and robust volume-based algorithm that evaluate flexure attribute more accurately and effectively. The algorithms first volumetrically fit a cubic surface by using a diamond 13-node grid cell to seismic data, and then compute flexure using the spatial derivatives of the built surface. To avoid introducing interpreter bias, this study introduces a new workflow for automatically building surfaces that best represent the geometry of seismic reflections. A dip-steering approach based on 3D complex seismic trace analysis is implemented to enhance the accuracy of surface construction and to reduce computational time. Applications to two 3D seismic surveys demonstrate the accuracy and efficiency of the new flexure algorithm for characterizing faults and fractures in fractured reservoirs.;For robust fracture detection, this study presents a new methodology to compute both magnitude and directions of most extreme flexure attribute. The new method first computes azimuthal flexure; and then implements a discrete azimuth-scanning approach to finding the magnitude and azimuth of most extreme flexure. Specially, a set of flexure values is estimated and compared by substituting all possible azimuths between 0 degree (Inline) and 180 degree (Crossline) into the newly-developed equation for computing azimuthal flexure. The added value of the new algorithm is demonstrated through applications to the seismic data set from Teapot Dome of Wyoming. The results indicate that most extreme flexure and its associated azimuthal directions help reveal structural complexities that are not discernible from conventional coherence or geometric attributes.;Given that the azimuth-scanning approach for computing maximum/minimum flexure is time-consuming, this study proposes fracture detection using most positive/negative flexures; since for gently-dipping structures, most positive is similar to maximum flexure while most negative flexure to minimum flexure. After setting the first reflection derivatives (or apparent dips) to be zero, the localized reflection is rotated to be horizontal and thereby the equation for computing azimuthal flexure is significantly simplified, from which a new analytical approach is proposed for computing most positive/negative flexures. Comparisons demonstrate that positive/negative flexures can provide quantitative fracture characterization similar to most extreme flexure, but the computation is 8 times faster than the azimuth-scanning approach.;Due to the overestimate by using most positive/negative flexure for fracture characterization, 3D surface rotation is then introduced for flexure extraction in the presence of structural dip, which makes it possible for solving the problem in an analytical manner. The improved computational efficiency and accuracy is demonstrated by both synthetic testing and applications to real 3D seismic datasets, compared to the existing discrete azimuth-scanning approach.;Last but not the least, strain analysis is also important for understanding structural deformation, predicting natural fracture system, and planning well bores. Physically, open fractures are most likely to develop in extensional domains whereas closed fractures in compressional ones. The beam model has been proposed for describing the strain distribution within a geological formation with a certain thickness, in which, however, the extensional zone cannot be distinguished from the compression one with the aid of traditional geometric attributes, including discontinuity, dip, and curvature. To resolve this problem, this study proposes a new algorithm for strain reconstruction using apparent dips at each sample location within a seismic cube

A comparative study of texture attributes for characterizing subsurface structures in seismic volumes

In this paper, we explore how to computationally characterize subsurface geological structures presented in seismic volumes using texture attributes. For this purpose, we conduct a comparative study of typical texture attributes presented in the image processing literature. We focus on spatial attributes in this study and examine them in a new application for seismic interpretation, i.e., seismic volume labeling. For this application, a data volume is automatically segmented into various structures, each assigned with its corresponding label. If the labels are assigned with reasonable accuracy, such volume labeling will help initiate an interpretation process in a more effective manner. Our investigation proves the feasibility of accomplishing this task using texture attributes. Through the study, we also identify advantages and disadvantages associated with each attribute

IgG glycosylation profile and the glycan score are associated with type 2 diabetes in independent Chinese populations: A case-control study

Background. The relationship between the IgG glycan panel and type 2 diabetes remains unclear in Chinese population. We aimed to investigate the association of the IgG glycan profile and glycan score with type 2 diabetes. Methods. In the discovery population, 162 individuals diagnosed with type 2 diabetes and 162 matched controls from Beijing health management cohort were included. We analyzed the IgG glycan profile and composed a glycan score for type 2 diabetes. Findings were validated in the replication population from Beijing Xuanwu community cohort (280 cases and 508 controls). Area under curve (AUC) using 10-fold and bootstrap validation, net reclassification index (NRI), and integrated discrimination index (IDI) were calculated for the glycan score. Results. In the discovery population, 5 initial IgG glycans and 7 derived traits were significantly associated with type 2 diabetes after Bonferroni correction and Lasso selection, which were validated in the replication population subsequently. The glycan score composed of these IgG glycans and traits showed a strong association with type 2 diabetes (combined odds ratio (OR): 3.78) and its risk factors. In the replication population, AUC of the model involving clinical traits improved from 0.74 to above 0.90, and the values of NRI and IDI were 0.35 and 0.42, respectively, with the glycan score added. Conclusions. IgG glycosylation profiles were associated with type 2 diabetes and the glycan score may be a novel indicator for diabetes which reflected a proinflammatory status

Dashing and Star: Byzantine Fault Tolerance with Weak Certificates

State-of-the-art Byzantine fault-tolerant (BFT) protocols assuming partial synchrony such as SBFT and HotStuff use \textit{regular certificates} obtained from $2f+1$ (partial) signatures. We show that one can use \textit{weak certificates} obtained from only $f+1$ signatures to \textit{assist} in designing more robust and more efficient BFT protocols. We design and implement two BFT systems: Pichu (a family of two HotStuff-style BFT protocols) and Sonic (a parallel BFT framework). We first present Pichu1 that targets both efficiency and robustness using weak certificates. Pichu1 is also network-adaptive in the sense that it can leverage network connection discrepancy to improve performance. We show that Pichu1 outperforms HotStuff in various failure-free and failure scenarios. We then present Pichu2 enabling a \textit{one-phase} fast path by using \textit{strong certificates} from $3f+1$ signatures. We then leverage weak certificates to build Sonic, a highly scalable BFT framework that delivers transactions from $n-f$ replicas. Sonic compares favorably with existing protocols in terms of liveness, communication, state transfer, scalability, and/or robustness under failures. We demonstrate that Pichu achieves 47\%-107\% higher peak throughput than HotStuff for experiments on Amazon EC2. Meanwhile, unlike all known BFT protocols whose performance degrades as $f$ grows large, the peak throughput of Sonic increases as $f$ grows. When deployed in a WAN with 91 replicas across five continents, Sonic achieves an impressive throughput of 256 ktx/sec, 2.38x that of Narwhal

Circulating TRAIL Shows a Significant Post-Partum Decline Associated to Stressful Conditions

Background: Since circulating levels of TNF-related apoptosis inducing ligand (TRAIL) may be important in the physiopathology of pregnancy, we tested the hypothesis that TRAIL levels change at delivery in response to stressful conditions. Methods/Principal Findings: We conducted a longitudinal study in a cohort of 73 women examined at week 12, week 16, delivery and in the corresponding cord blood (CB). Serum TRAIL was assessed in relationship with maternal characteristics and to biochemical parameters. TRAIL did not vary between 12 (67.6627.6 pg/ml, means6SD) and 16 (64.0616.2 pg/ml) weeks ’ gestation, while displaying a significant decline after partum (49.3626.4 pg/ml). Using a cut-off decline.20 pg/ml between week 12 and delivery, the subset of women with the higher decline of circulating TRAIL (41.7%) showed the following characteristics: i) nullipara, ii) higher age, iii) operational vaginal delivery or urgent CS, iv) did not receive analgesia during labor, v) induced labor. CB TRAIL was significantly higher (131.6652 pg/ml) with respect to the corresponding maternal TRAIL, and the variables significantly associated with the first quartile of CB TRAIL (,90 pg/ml) were higher prepregnancy BMI, induction of labor and fetal distress. With respect to the biochemical parameters, maternal TRAIL at delivery showed an inverse correlation with C-reactive protein (CRP), total cortisol, glycemia and insulin at bivariate analysis, but only with CRP at multivariate analysis