73 research outputs found
Descriptive statistics and probability distributions of volumetric parameters of a Nigerian heavy oil and bitumen deposit
The absence of geostatistical modeling of volumetric parameters of the long-discovered Nigerian heavy oil and bitumen
deposits is responsible for the inconsistencies surrounding estimates of hydrocarbon-in-place contained therein. An exploratory
data analysis (EDA) is a pre-cursor to such modeling. As part of EDA, this work presents the descriptive statistics and
probability distributions of the volumetric parameters of a Nigerian heavy oil and bitumen deposit. Raw data from the existing
works have been assembled into a database. Using basic principles, porosity have been computed, from the raw data, for
several core samples retrieved from the two bituminous horizons in the deposit. The computed database has been partitioned
into the two horizons, using depth-to-top and thickness data. Furthermore, this work has conducted detailed analyses and
offers robust discussions on the descriptive statistics and probability distributions of the porosity, depth-to-top, and thickness
databases. The statistics and distribution curves obtained are observed to exhibit good correlations with existing geologic,
stratigraphic, and textural data. An hypothesis suggesting the two horizons belong to same geological population has been
formulated and tested at field and well levels; with results affirming the hypothesis. The descriptive statistics and probability
distributions obtained offer a significant understanding of the characteristics and features of the available data. In addition,
the distributions now become prior information to which reservoir descriptions would be constrained, in the future conditional
simulation stage of this work. The correlation of core data obtained here with the existing geologic, stratigraphic, and
textural data would promote data integration in the characterization of this deposit
Sampling Grid Shifting Algorithm: A Non-ergodic Spatial Bootstrap Technique for Regular and Irregular Sampling Patterns
Accounting for uncertainty in statistical model parameters is an essential part of
geostatiscal reservoir characterization. While parameter uncertainty may be assessed in
its ergodic form; the non-ergodic is a better characterization of the variability in the
random field. Assessing non-ergodic parameter uncertainty requires re-sampling
(bootstrapping) techniques. Existing techniques for such non-ergodic re-sampling are
plagued with some limitations/complications. This paper therefore presents a spatial
bootstrap algorithm that overcomes the limitations/complication. For a discretized field,
the algorithm implements simultaneous displacements (shiftings) of all sampling points
through the same distance vector. The shiftings are done across the dimensions of the
field subject to the dimensionality of the sampling. In each dimension, the sampling
points are shifted successively through a distance equivalent to the gridblock length in
that dimension. At each shifting, a shifted sampling grid, of similar configuration as the
original sampling grid, is generated. Using the shifted sampling grid, the algorithm resamples
a full-grid simulated realization of the field. The assumption of second-order
stationarity implies that a sample from a shifted sampling grid is considered a repeated
sample of the original sample. The algorithm has been scripted in R statistical
computing environment and applied to an irregularly-sampled 3-D field with satisfactory
results
Reservoir Characterization, variogram estimate, machine learning, Upstream Oil & Gas, agbabu field porosity data, variogram cloud plot, porosity data, estimation, variogram model, variogram
Deposits of heavy oil and natural bitumen have been long-discovered in the Dahomey basin south-western Nigeria. However, inconsistency in estimates of volumes of hydrocarbon contained in these deposits has inhibited commercial interest in the deposits. The inconsistency is attributable to the little or no consideration for spatial variability in those studies. This work is therefore motivated by the need for spatially-coherent geomodels leading to reliable volumetric estimates. An existing database of porosity, depth-to-top and thickness attributes of a section of the deposits located at Agbabu is the subject of this work.
This work conducted exploratory spatial data analysis (ESDA) as well as empirical variogram estimation, interpretation and modeling of the attributes. Here, the estimation and interpretation of empirical variogram faced a number of challenges with potentials to render the estimates uninterpretable, unstable and inconsistent with geologic information. These include presence of spatial outlier data, clusteredness of variogram clouds, data paucity, and irregular distribution of point-pairs on variogram clouds. Spatial outliers were either removed or correlated with existing geologic information. The clusteredness issues were resolved using a machine-learning – aided variogram estimation technique recently proposed. Variogram cloud binning approach was deployed to handle irregular distribution of point-pairs. In attempting to deploy an automatic fitting algorithm, cases of insufficient empirical points leading to lack of convergence were encountered. Such cases were resolved by adopting a combination of manual and automatic fitting approaches.
Ultimately, this work presents a three-dimensional anisotropic (zonal) porosity variogram model and two-dimensional anisotropic (geometric) models for the depth-to-top and thickness variograms. These models are suitable inputs to spatial interpolation algorithms in generating maps of these volumetric attributes
Evaluation of changes in sexual response and factors influencing sexuality during pregnancy among Nigerian women in Jos, Nigeria
Background: Pregnancy is characterized by physical, hormonal and psychological changes that could influence women’s sexuality. The study aimed at ascertaining changes in the women’s sexual domains as well as factors affecting their sexual responses.Methods: A total of 177 healthy heterosexual pregnant Nigerian women at term and in stable marital relationships were included in the study. Authors’ designed structured questionnaire featuring socio-demographic and obstetric characteristics as well as assessment of their sexual desire, arousal, orgasm, sexual satisfaction and pain compared to the pre-pregnancy period was used to collect the information. Data was analyzed using SPSS version 16 for windows.Results: Mean age of the women was 30.9 ± 4.7 years. Majority of them reported decline in sexual desire, arousal, frequency of orgasm and sexual satisfaction compared to the pre-pregnancy period. Reduce sexual desire was marked in the first trimester but sexual desire peaked in second trimester. Women aged ≥31 years were four times more likely to experience increase frequency of orgasm (OR 4.0, 95% CI 1.9 – 8.7, P = 0.02) while those with tertiary education (OR 2.2, 95% CI 1.1 – 4.2, P = 0.02) and unplanned pregnancy (OR 2.4, 95% CI 1.8 – 5.0, P = 0.04) were more likely to experience decreased sexual satisfaction compared to the pre-pregnancy period.Conclusions: Pregnancy is associated with decline in all domains of female sexual response cycle among the women. Older maternal age positively impacts on frequency of attainment of orgasm while tertiary educational level and unplanned pregnancy negatively affect their sexual satisfaction during pregnancy
Reservoir Characterization, variogram estimate, machine learning, Upstream Oil & Gas, agbabu field porosity data, variogram cloud plot, porosity data, estimation, variogram model, variogram
Deposits of heavy oil and natural bitumen have been long-discovered in the Dahomey basin south-western Nigeria. However, inconsistency in estimates of volumes of hydrocarbon contained in these deposits has inhibited commercial interest in the deposits. The inconsistency is attributable to the little or no consideration for spatial variability in those studies. This work is therefore motivated by the need for spatially-coherent geomodels leading to reliable volumetric estimates. An existing database of porosity, depth-to-top and thickness attributes of a section of the deposits located at Agbabu is the subject of this work.
This work conducted exploratory spatial data analysis (ESDA) as well as empirical variogram estimation, interpretation and modeling of the attributes. Here, the estimation and interpretation of empirical variogram faced a number of challenges with potentials to render the estimates uninterpretable, unstable and inconsistent with geologic information. These include presence of spatial outlier data, clusteredness of variogram clouds, data paucity, and irregular distribution of point-pairs on variogram clouds. Spatial outliers were either removed or correlated with existing geologic information. The clusteredness issues were resolved using a machine-learning – aided variogram estimation technique recently proposed. Variogram cloud binning approach was deployed to handle irregular distribution of point-pairs. In attempting to deploy an automatic fitting algorithm, cases of insufficient empirical points leading to lack of convergence were encountered. Such cases were resolved by adopting a combination of manual and automatic fitting approaches.
Ultimately, this work presents a three-dimensional anisotropic (zonal) porosity variogram model and two-dimensional anisotropic (geometric) models for the depth-to-top and thickness variograms. These models are suitable inputs to spatial interpolation algorithms in generating maps of these volumetric attributes
Ergodic and non-ergodic variogram uncertainty in Agbabu bitumen field porosity data
A recent investigation estimated and modeled the variogram of the porosity attribute of the bitumen field located at Agbabu, south-west Nigeria. In spite of methodological interventions made during the estimation, the variogram estimates obtained are still uncertain due to preferential
and limited sample data. This current research therefore assesses the uncertainty in the ergodic and non-ergodic variogram estimates. Multiple samples required for ergodic and non-ergodic variogram estimates have been drawn from simulated realizations of the porosity random field.
Variogram estimates have been obtained (using a recently-formulated lag-cluster technique and conventional technique) for each sample. The sampling distributions of these estimates have been examined with histograms and Normal Q-Q plots. The estimates exhibit approximately Normal
distributions. The uncertainty in the ergodic variogram increases from 1.4Ă—10-7 at lag 16.7 m to 4.6Ă—10-7 at lag 4601.4 m; thereafter, it appears to flatten out. For most lag distances, the uncertainty in the non-ergodic variogram is constant at about 1.8Ă—10-7; it fluctuates at large lag
distances. The uncertainty in non-ergodic estimates is observed to be lower than the uncertainty in ergodic estimates. Consequently, that the current wel
Optimal PMU Placement Using Genetic Algorithm for 330kV 52-Bus Nigerian Network
The phasor Measurement Unit is a modern tracking tool mounted on a network to track
and manage power systems. PMU is accurate and time-synchronized device that gives
voltage phasor measurements in nodes and current phasor measurements connected to
those nodes where the PMU is installed. This study introduces the Genetic Algorithm for
optimization of allocation of PMUs to enable maximum observation of the power network.
The optimal PMU placement (OPP) problem is developed to minimize the quantity of PMU
to be placed. The set and optimized model can efficiently position PMU in any network,
considering the regular operation and zero injection (ZIN). Thus, the allocation algorithm
implemented on IEEE 14-bus systems, the result was compared to that of existing works
which achieved the same system of redundancy index. As a further study, the proposed
approach is applied to the Nigerian 330kV new 52-bus systems, under operational
arrangements for maximum observability of the network system. The technique formulated
to handle normal operation and zero injection node succeeded in producing comparable
results with other available techniques
Subordinate Effect of -21M HLA-B Dimorphism on NK Cell Repertoire Diversity and Function in HIV-1 Infected Individuals of African Origin
Natural Killer (NK) cells play an important role in antiviral defense and their potent effector function identifies them as key candidates for immunotherapeutic interventions in chronic viral infections. Their remarkable functional agility is achieved by virtue of a wide array of germline-encoded inhibitory and activating receptors ensuring a self-tolerant and tunable repertoire. NK cell diversity is generated by a combination of factors including genetic determinants and infections/environmental factors, which together shape the NK cell pool and functional potential. Recently a genetic polymorphism at position -21 of HLA-B, which influences the supply of HLA-E binding peptides and availability of HLA-E for recognition by the inhibitory NK cell receptor NKG2A, was shown to have a marked influence on NK cell functionality in healthy human cytomegalovirus (HCMV) seronegative Caucasian individuals. In this study, -21 methionine (M)-expressing alleles supplying HLA-E binding peptides were largely poor ligands for inhibitory killer immunoglobulin-like receptors (KIRs), and a bias to NKG2A-mediated education of functionally-potent NK cells was observed. Here, we investigated the effect of this polymorphism on the phenotype and functional capacity of peripheral blood NK cells in a cohort of 36 African individuals with human immunodeficiency virus type 1 (HIV-1)/HCMV co-infection. A similarly profound influence of dimorphism at position -21 of HLA-B on NK cells was not evident in these subjects. They predominantly expressed African specific HLA-B and -C alleles that contribute a distinct supply of NKG2A and KIR ligands, and these genetic differences were compounded by the marked effect of HIV-1/HCMV co-infection on NK cell differentiation. Together, these factors resulted in a lack of correlation of the HLA-B -21 polymorphism with surface abundance of HLA-E and loss of the NK cell functional advantage in subjects with -21M HLA-B alleles. Instead, our data suggest that during HIV/HCMV co-infection exposure of NK cells to an environment that displays altered HLA-E ligands drives adaptive NKG2C+ NK cell expansions influencing effector responses. Increased efforts to understand how NK cells are functionally calibrated to self-HLA during chronic viral infections will pave the way to developing targeted therapeutic interventions to overcome the current barriers to enhancing immune-based antiviral control
Improving postpartum care delivery and uptake by implementing context-specific interventions in four countries in Africa: a realist evaluation of the Missed Opportunities in Maternal and Infant Health (MOMI) project.
Postpartum care (PPC) has remained relatively neglected in many interventions designed to improve maternal and neonatal health in sub-Saharan Africa. The Missed Opportunities in Maternal and Infant Health project developed and implemented a context-specific package of health system strengthening and demand generation in four African countries, aiming to improve access and quality of PPC. A realist evaluation was conducted to enable nuanced understanding of the influence of different contextual factors on both the implementation and impacts of the interventions. Mixed methods were used to collect data and test hypothesised context-mechanism-outcome configurations: 16 case studies (including interviews, observations, monitoring data on key healthcare processes and outcomes), monitoring data for all study health facilities and communities, document analysis and participatory evaluation workshops. After evaluation in individual countries, a cross-country analysis was conducted that led to the development of four middle-range theories. Community health workers (CHWs) were key assets in shifting demand for PPC by 'bridging' communities and facilities. Because they were chosen from the community they served, they gained trust from the community and an intrinsic sense of responsibility. Furthermore, if a critical mass of women seek postpartum healthcare as a result of the CHWs bridging function, a 'buzz' for change is created, leading eventually to the acceptability and perceived value of attending for PPC that outweighs the costs of attending the health facility. On the supply side, rigid vertical hierarchies and defined roles for health facility workers (HFWs) impede integration of maternal and infant health services. Additionally, HFWs fear being judged negatively which overrides the self-efficacy that could potentially be gained from PPC training. Instead the main driver of HFWs' motivation to provide comprehensive PPC is dependent on accountability systems for delivering PPC created by other programmes. The realist evaluation offers insights into some of the contextual factors that can be pivotal in enabling the community-level and service-level interventions to be effective
Treatment of COVID-19 with remdesivir in the absence of humoral immunity: a case report
The response to the coronavirus disease 2019 (COVID-19) pandemic has been hampered by lack of an effective severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antiviral therapy. Here we report the use of remdesivir in a patient with COVID-19 and the prototypic genetic antibody deficiency X-linked agammaglobulinaemia (XLA). Despite evidence of complement activation and a robust T cell response, the patient developed persistent SARS-CoV-2 pneumonitis, without progressing to multi-organ involvement. This unusual clinical course is consistent with a contribution of antibodies to both viral clearance and progression to severe disease. In the absence of these confounders, we take an experimental medicine approach to examine the in vivo utility of remdesivir. Over two independent courses of treatment, we observe a temporally correlated clinical and virological response, leading to clinical resolution and viral clearance, with no evidence of acquired drug resistance. We therefore provide evidence for the antiviral efficacy of remdesivir in vivo, and its potential benefit in selected patients
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