Case studies in causal inference and anomaly detection

The study of parent-child well interactions in unconventional shales has generated high interest both in the industry and academia over the last decade. This is largely because of the growing number of child wells and their immediate impact on the parent well production owing to several dynamic factors, one of them, including well spacing. Evaluating the impact of well spacing on parent and child well production performance is challenging. Several studies have resorted to geomechanical stress and fracture modeling combined with dynamic simulation techniques while a few operators have chosen field trials to evaluate optimal well spacing. Several data-driven approaches to address the well-spacing problem have also become popular. One such commonly used data-driven approach simply calculates the difference in cumulative production over a specified period of time for parent and child wells grouped by spacing. This approach has been the method of choice for several different recent analyses of well spacing; however, given that the method of simple averages does not account for formation properties or completion design, the results may be compromised and can lead to counterintuitive results. In this thesis, I introduce a new data-driven approach leveraging the power of causal inference as seen in clinical trials for multivariate observational studies. The causal approach addresses the problem behind the routinely used simple averages approach by providing a formalism to control for reservoir and completion variables when evaluating the impact of well spacing on production performance. I apply the causal inference workflow to a dataset from a prolific oil basin in Texas with over 700 wells in the analyses. It includes the formation properties, fluid volume, proppant weight, landing zones and the downhole locations of the wells. Using the causal inference workflow, I evaluate the effect of well spacing on well performance at different parent-child spacing ranges. The optimal well spacing is then estimated for this shale play based on the magnitude of the causal effects. These estimates are then compared with the simple averages approach to demonstrate the power and utility of causality. In the second part of the thesis, I transition into a discussion on anomaly detection approaches applied in the oil and gas industry. I discuss current anomaly detection methods for a widely used artificial lift method – the Sucker Rod Pump (SRP). Today, there is a growing need for fast and accurate anomaly detection systems given the emergence of Internet of Things (IoT) and access to Big Data. Anomaly detection using human operators can be expensive, is often subject to bias and experience-levels and does not scale very well with the need to monitor more than a few tens of wells. With SRPs, the problem of anomaly detection becomes a problem of image classification where dynamometer cards are evaluated for signatures of failure. While this has been the mainstay of anomaly detection for pumpjacks, in this thesis, I automate this task of monitoring and detecting the anomalies from the SRP pump cards. Several thousand synthetic pump cards specific to pump failures modes are generated from the literature and fed to a deep learning model. This deep learning model is a Convolutional Neural Network (CNN) which is commonly used in image classification tasks, speech recognition tasks as well as many other modern-day technology applications including smart phones, self-driving cars, aerospace etc. The CNN used in this work offers a very high accuracy for detecting a variety of pump failures modes thereby offering the potential to save costs, time and unnecessary workovers for the operator

First principles calculation of polarization induced interfacial charges in GaN/AlN heterostructures

We propose a new method to calculate polarization induced interfacial charges in semiconductor heterostructures using classical electrostatics applied to real-space band diagrams from first principles calculations and apply it to GaN/AlN heterostructures with ultrathin AlN layers (4-6 monolayers). We show that the calculated electric fields and interfacial charges are independent of the exchange-correlation functionals used (local-density approximation and hybrid functionals). We also find the calculated interfacial charge of (6.8 +/- 0.4) x 10^13 cm-2 to be in excellent agreement with experiments and the value of 6.58 x 10^13 cm-2 calculated from bulk polarization constants, validating the use of bulk constants even for very thin films.Comment: 3 pages, 2 figures; submitted to Applied Physics Letter

Finite Element Study on the Effect of Geometrical Parameters on the Mechanical Behavior of 3D Reentrant Auxetic Honeycombs.

Abstract Auxetic materials are a special case of cellular materials, which exhibit a negative Poisson’s ratio. This in fact is the reason behind their peculiar behavior i.e. lateral shrinkage under longitudinal compression and vice versa. Since these materials do not obey the laws of “normal” materials and go beyond common sense, they are still an emerging class which can be put to use for various purposes like self-locking reinforcing fibers in composites, controlled release media, self-healing films, piezoelectric sensors, and also be used in biomedical engineering. Their stress-strain behavior, Poisson’s ratio and impact energy absorption are controlled by bulk material as well as the unit cell geometry. Among many forms of auxetic structures available, we have chosen a three-dimensional reentrant auxetic honeycomb unit cell. The unit cell geometrical parameters were taken from literature. In this study, we try to understand the effects of strut angle through finite element simulations while keeping the bulk material, unit cell size, strut thickness and number of repetitions constant. A total of three different angles were tested, based on which we conclude that as angle increases, the Poisson’s ratio increases and Energy absorption is maximum at 30 deg

COMPARISON OF POST-LICENSURE SAFETY SURVEILLANCE OF BIVALENT AND QUADRIVALENT HUMAN PAPILLOMAVIRUS VACCINES IN HEALTHY MUMBAI WOMEN

Objective: This study is the first comprehensive effort after HPV vaccine controversy in INDIA to compare two HPV vaccines without vaccine manufacturers funding in single, randomized, well-defined population of healthy married women aged 18-25 years using identical methodology for assessment.Methods: The study protocol was approved by an institutional ethical review committee and registered in Clinical trial registry of INDIA prior to subject recruitment. Total 77 women were screened but 69 were randomized to receive either HPV2 or HPV4 vaccines.Results: According to the present study, both HPV vaccines were well tolerated without any serious vaccine-related adverse event. Adverse drug reactions reported for both HPV vaccinations were 22 (35.48%) after the ï¬rst dose, 7 (12.05%) after the second dose and 11 (25%) after the third dose. After bivalent and quadrivalent HPV vaccination, 29 and 11 adverse drug events were recorded within seven days after any HPV vaccine dose respectively. Most frequently reported solicited local symptom from both groups was34 injection site pain which was mild in intensity.Conclusion: Both HPV vaccines appear to be safe, HPV4 being more cost-effective. However, large scale post-marketing studies are needed in view of amount of disease burden.Â

Prospecting the theragnostic potential of the psycho-neuro-endocrinological perturbation of the gut-brain-immune axis for improving cardiovascular diseases outcomes

Biological derivatives and their effective influence on psychological parameters are increasingly being deciphered to better understand body-mind perspectives in health. Recent evidence suggests that the gut-brain immune axis is an attractive theragnostic target due to its innate capacity to excite the immune system by activating monocyte exosomes. These exosomes induce spontaneous alterations in the microRNAs within the brain endothelial cells, resulting in an acute inflammatory response with physiological and psychological sequelae, evidenced by anxiety and depression. Exploring the role of the stress models that influence anxiety and depression may reflect on the effect and role of exosomes, shedding light on various physiological responses that explain the contributing factors of cardiovascular disorders. The pathophysiological effects of gut-microbiome dysbiosis are further accentuated by alterations in the glucose metabolism, leading to type 2 diabetes, which is known to be a risk factor for cardiovascular disorders. Understanding the role of exosomes and their implications for cell-to-cell communication, inflammatory responses, and neuronal stress reactions can easily provide insight into the gut-brain immune axis and downstream cardiovascular sequelae

Science in the wilderness: the predicament of scientific research in India’s wildlife reserves

Ecology and allied scientific disciplines aim to understand patterns and processes pertaining to wild species, their ecosystems and their relationships with humans. India’s wildlife reserves are important ‘living laboratories’ for these disciplines. Today, there is a disturbing trend across India where scientists are increasingly denied access to wildlife reserves for scientific research or are seriously impeded, without scope for redress. Although official wildlife management rhetoric emphasizes the need for scientific research, in reality, it is viewed as undesirable and permitted, if at all, as a concession, subject to the discretion of individual forest officials. With no enabling legislative or policy framework to promote and apply science in our wildlife reserves, we are concerned that the future of many scientific disciplines in India is being jeopardized. Here, we provide an analysis of this issue and outline steps needed to promote scientific research in our natural areas

Exosomal microRNAs in breast cancer: towards theranostic applications

Breast cancer is one of the top two reproductive cancers responsible for high rates of morbidity and mortality among women globally. Despite the advancements in the treatment of breast cancer, its early diagnosis remains a challenge. Recent evidence indicates that despite the adroit use of numerous strategies to facilitate rapid and precision-oriented screening of breast cancer at the community level through the use of mammograms, Fine-needle aspiration cytology (FNAC) and biomarker tracking, no strategy has been unequivocally accepted as a gold standard for facilitating rapid screening for disease. This necessitates the need to identify novel strategies for the detection and triage of breast cancer lesions at higher rates of specificity, and sensitivity, whilst taking into account the epidemiologic and social-demographic features of the patients. Recent shreds of evidence indicate that exosomes could be a robust source of biomaterial for the rapid screening of breast cancer due to their high stability and their presence in body fluids. Increasing evidence indicates that the Exosomal microRNAs- play a significant role in modifying the tumour microenvironment of breast cancers, thereby potentially aiding in the proliferation, invasion and metastasis of breast cancer. In this review, we summarize the role of ExomiRs in the tumour microenvironment in breast cancer. These ExomiRs can also be used as candidate biomarkers for facilitating rapid screening and triaging of breast cancer patients for clinical intervention