Predict the flow of well fluids : a big data approach

Master's thesis in Computer scienceIn the oil and gas industry, millions of records of data are registered every day. The data is composed by a mix of structured and unstructured sources. For example downhole gauges and wellhead sensors are logging pressure and temperature in different places of the well. Emerging technologies such as fiber-optic, wireless communication, allow the sensors to be digital, more accurate and reliable. The number of sensors as well as their resolution increase, which imposes new challenges in terms of amount of data that is necessary to be processed. Moreover, engineers in oil and gas industry store well operations, interventions logs and their interpretation in different files and formats. Combining and analyzing these different types of data is a worthy challenge for each company to obtain valuable information. The production/performance engineers need the production rates to monitor the well situation and optimize the well performance. However, in a production well, the well production rates are not determined in real time. To measure the fluid rates Well Test operation is carried out periodically, normally once a month. However, these rates might change dramatically within two Well Test. For this reason, a model that can predict the fluid rates, gives great advantages to the production engineers to optimize the well performance in real time. In this thesis a real usecase of an oil well was studied and an approach was proposed to process and analysis a large amount of structured and unstructured data using Exploratory Data Analysis (EDA) and design an Artificial Neural Network (ANN) to predict the flow of the well fluids. The usefulness of this method has been proved by predicting the rates of the well fluids for the usecase with reasonable low errors. Moreover, we proposed a second approach that increased even more the network accuracy[lower errors].ConocoPhillip

StarMX: A Framework for Developing Self-Managing Software Systems

The scale of computing systems has extensively grown over the past few decades in order to satisfy emerging business requirements. As a result of this evolution, the complexity of these systems has increased significantly, which has led to many difficulties in managing and administering them. The solution to this problem is to build systems that are capable of managing themselves, given high-level objectives. This vision is also known as Autonomic Computing. A self-managing system is governed by a closed control loop, which is responsible for dynamically monitoring the underlying system, analyzing the observed situation, planning the recovering actions, and executing the plan to maintain the system equilibrium. The realization of such systems poses several developmental and operational challenges, including: developing their architecture, constructing the control loop, and creating services that enable dynamic adaptation behavior. Software frameworks are effective in addressing these challenges: they can simplify the development of such systems by reducing design and implementation efforts, and they provide runtime services for supporting self-managing behavior. This dissertation presents a novel software framework, called StarMX, for developing adaptive and self-managing Java-based systems. It is a generic configurable framework based on standards and well-established principles, and provides the required features and facilities for the development of such systems. It extensively supports Java Management Extensions (JMX) and is capable of integrating with different policy engines. This allows the developer to incorporate and use these techniques in the design of a control loop in a flexible manner. The control loop is created as a chain of entities, called processes, such that each process represents one or more functions of the loop (monitoring, analyzing, planning, and executing). A process is implemented by either a policy language or the Java language. At runtime, the framework invokes the chain of processes in the control loop, providing each one with the required set of objects for monitoring and effecting. An open source Java-based Voice over IP system, called CC2, is selected as the case study used in a set of experiments that aim to capture a solid understanding of the framework suitability for developing adaptive systems and to improve its feature set. The experiments are also used to evaluate the performance overhead incurred by the framework at runtime. The performance analysis results show the execution time spent in different components, including the framework itself, the policy engine, and the sensors/effectors. The results also reveal that the time spent in the framework is negligible, and it has no considerable impact on the system's overall performance

New insights into the clinical and molecular spectrum of the novel CYFIP2-related neurodevelopmental disorder and impairment of the WRC-mediated actin dynamics

PURPOSE A few de novo missense variants in the cytoplasmic FMRP-interacting protein 2 (CYFIP2) gene have recently been described as a novel cause of severe intellectual disability, seizures, and hypotonia in 18 individuals, with p.Arg87 substitutions in the majority. METHODS We assembled data from 19 newly identified and all 18 previously published individuals with CYFIP2 variants. By structural modeling and investigation of WAVE-regulatory complex (WRC)-mediated actin polymerization in six patient fibroblast lines we assessed the impact of CYFIP2 variants on the WRC. RESULTS Sixteen of 19 individuals harbor two previously described and 11 novel (likely) disease-associated missense variants. We report p.Asp724 as second mutational hotspot (4/19 cases). Genotype-phenotype correlation confirms a consistently severe phenotype in p.Arg87 patients but a more variable phenotype in p.Asp724 and other substitutions. Three individuals with milder phenotypes carry putative loss-of-function variants, which remain of unclear pathogenicity. Structural modeling predicted missense variants to disturb interactions within the WRC or impair CYFIP2 stability. Consistent with its role in WRC-mediated actin polymerization we substantiate aberrant regulation of the actin cytoskeleton in patient fibroblasts. CONCLUSION Our study expands the clinical and molecular spectrum of CYFIP2-related neurodevelopmental disorder and provides evidence for aberrant WRC-mediated actin dynamics as contributing cellular pathomechanism

Severe reaction to radiotherapy provoked by hypomorphic germline mutations in ATM (ataxia–telangiectasia mutated gene)

Background: A minority of breast cancer (BC) patients suffer from severe reaction to adjuvant radiotherapy (RT). Although deficient DNA double-strand break repair is considered the main basis for the reactions, pretreatment identification of high-risk patients has been challenging. Methods: To retrospectively determine the etiology of severe local reaction to RT in a 39-year-old woman with BC, we performed next-generation sequencing followed by further clinical and functional studies. Results: We found a −4 intronic variant (c.2251-4A>G) in trans with a synony-mous (c.3576G>A) variant affecting the ATM DNA-repair gene (NG_009830.1, NM_000051.3) which is linked to autosomal recessive ataxia–telangiectasia (A–T). We verified abnormal transcripts resulting from both variants, next to a minor wild-type transcript leading to a residual ATM kinase activity and genomic instability. Follow-up examination of the patient revealed no classic sign of A–T but previously unnoticed head dystonia and mild dysarthria, a family history of BC and late-onset ataxia segregating with the variants. Additionally, her serum level of alpha-fetopro-tein (AFP) was elevated similar to A–T patients. Conclusion: Considering the variable presentations of A–T and devastating impact of severe reactions to RT, we suggest a routine measurement of AFP in RT-candidate BC patients followed by next-generation sequencing with special attention to non-canonical splice site and synonymous variants in ATM

Genotype-phenotype evaluation of MED13L defects in the light of a novel truncating and a recurrent missense mutation

A decade after the designation of MED13L as a gene and its link to intellectual disability (ID) and dextro-looped transposition of great arteries in 2003, we previously described a recognizable syndrome due to MED13L haploinsufficiency. Subsequent reports of 22 further patients diagnosed by genome-wide testing further delineated the syndrome with expansion of the phenotypic spectrum and showed reduced penetrance for congenital heart defects. We now report two novel patients identified by whole exome sequencing, one with a de novo MED13L truncating mutation and the other with a de novo missense mutation. The first patient indicates some facial resemblance to Kleefstra syndrome as a novel differential diagnosis, and the second patient shows, for the first time, recurrence of a MED13L missense mutation (p.(Asp860Gly)). Notably, our in silico modelling predicted this missense mutation to decrease the stability of an alpha-helix and thereby affecting the MED13L secondary structure, while the majority of published missense mutations remain variants of uncertain significance. Review of the reported patients with MED13L haploinsufficiency indicates moderate to severe ID and facial anomalies in all patients, as well as severe speech delay and muscular hypotonia in the majority. Further common signs include abnormal MRI findings of myelination defects and abnormal corpus callosum, ataxia and coordination problems, autistic features, seizures/abnormal EEG, or congenital heart defects, present in about 20–50% of the patients. With reference to facial anomalies, the majority of patients were reported to show broad/prominent forehead, low set ears, bitemporal narrowing, upslanting palpebral fissures, depressed/flat nasal bridge, bulbous nose, and abnormal chin, but macroglossia and horizontal eyebrows were also observed in ∼30%. The latter are especially important in the differential diagnosis of 1p36 deletion and Kleefstra syndromes, while the more common facial gestalt shows some resemblance to 22q11.2 deletion syndrome. Despite the fact that MED13L was found to be one of the most common ID genes in the Deciphering Developmental Disorders Study, further detailed patient descriptions are needed to explore the full clinical spectrum, potential genotype-phenotype correlations, as well as the role of missense mutations and potential mutational hotspots along the gene

Severe reaction to radiotherapy provoked by hypomorphic germline mutations in ATM (ataxia–telangiectasia mutated gene)

Background: A minority of breast cancer (BC) patients suffer from severe reaction to adjuvant radiotherapy (RT). Although deficient DNA double-strand break repair is considered the main basis for the reactions, pretreatment identification of high-risk patients has been challenging. Methods: To retrospectively determine the etiology of severe local reaction to RT in a 39-year-old woman with BC, we performed next-generation sequencing followed by further clinical and functional studies. Results: We found a −4 intronic variant (c.2251-4A>G) in trans with a synony-mous (c.3576G>A) variant affecting the ATM DNA-repair gene (NG_009830.1, NM_000051.3) which is linked to autosomal recessive ataxia–telangiectasia (A–T). We verified abnormal transcripts resulting from both variants, next to a minor wild-type transcript leading to a residual ATM kinase activity and genomic instability. Follow-up examination of the patient revealed no classic sign of A–T but previously unnoticed head dystonia and mild dysarthria, a family history of BC and late-onset ataxia segregating with the variants. Additionally, her serum level of alpha-fetopro-tein (AFP) was elevated similar to A–T patients. Conclusion: Considering the variable presentations of A–T and devastating impact of severe reactions to RT, we suggest a routine measurement of AFP in RT-candidate BC patients followed by next-generation sequencing with special attention to non-canonical splice site and synonymous variants in ATM

Generation and characterization of an endogenously tagged SPG11-human iPSC line by CRISPR/Cas9 mediated knock-in

Pathogenic bi-allelic variants in the SPG11 gene result in rare motor neuron disorders such as Hereditary Spastic Paraplegia type 11, Charcot-Marie Tooth, and Juvenile Amyotrophic Lateral Sclerosis-5. The main challenge in SPG11-linked disease research is the lack of antibodies against SPG11 encoded spatacsin. Here, we describe the CRISPR/Cas9 mediated generation and validation of an endogenously tagged SPG11- human iPSC line that contains an HA tag at the C-terminus of SPG11. The line exhibits multi-lineage differentiation potential and holds promise for studying the role of spatacsin and for the elucidation of SPG11-associated pathogenesis