Integration of Advanced Logging Evaluation Techniques Proves Additional Reserves from Thin Bed, Low Resistivity Pay Formations

2021 ◽  
Author(s):  
Ying Chun Guan ◽  
Mona Rashaid ◽  
Laila Hayat ◽  
Qasim Dashti ◽  
Khaled Sassi ◽  
...  

Abstract The biggest clastic reservoir based in Kuwait has been facing evaluation challenges over the thick intervals of highly laminated thin hydrocarbon layers. Conventional wireline tools have a limitation on resolution when it comes to addressing these thin beds. Therefore, the reserves are usually underestimated, and thin pays are often overlooked. This paper presents the integration of a variety of advanced Wireline tools in order to correctly evaluate and compute reserves from these thin pay zones. Acquisition of the triaxial induction tool enabled the study of resistivity anisotropy and the identification of thin pay zones through the distinct reading of the resistivity of the thin sand reservoir. The thin layers have also been further validated using high resolution advanced thin bed analysis from image logs. Advanced spectroscopy and NMR data were used to quantitively define the sand and shale fractions within the thin beds. These measurements were critical to input to improve the resistivity interpretation followed by a reliable estimate of the saturation. High resolution dielectric measurements provided resistivity-independent saturation information enhancing the NMR interpretation using water-filled porosity which was a key input into the identification of the heavy oil presence in Burgan. The newly identified thin pay zones have been further validated using the fluid sampling confirming presence of hydrocarbons with greater understanding of its properties and uniquely quantifying the mobile fluid fractions. The additional available reserves can only be properly determined by combining data from multiple sources to achieve a comprehensive evaluation. Resistivity anisotropy was observed based on the separation of vertical and horizontal resistivities and was therefore investigated to understand its root-cause over different zones. By integrating the results from the dielectric dispersion measurements, the diffusion-based NMR data, spectroscopy data, borehole image interpretation and high-resolution sand count delineation of different lithologic units at a finer scale, we were able to identify thin bedded sand-shale intervals in addition to pin-pointing the heavy oil intervals. Hydrocarbon saturations of individual sand layers showed improvement in hydrocarbon volumes, improvement in permeabilities across the studied zones and increased net pay estimations by 12%. Results from the fluid sampling performed across the newly identified thin pays have validated the advanced logging interpretation results and the presence of hydrocarbons. These intervals were overlooked by the standard basic evaluation and the reservoir potential has been revisited following the latest integrated advanced results. By combining the results of all these advanced wireline answer products, we were able to properly identify and quantify the additional available reserves and therefore change the classification of these reservoirs from poor to excellent with new development plan in place. The paper demonstrates the value solution of the high vertical resolutions taking advantage of the latest advanced technologies to enhance the characterization of laminated thin beds. The integrated advanced solution has enabled improved reservoir potential by the identification of new pay zones initially overlooked by the standard basic measurements.

2021 ◽  
Vol 13 (21) ◽  
pp. 4361
Author(s):  
Luca Ferrari ◽  
Fabio Dell’Acqua ◽  
Peng Zhang ◽  
Peijun Du

Automated extraction of buildings from Earth observation (EO) data is important for various applications, including updating of maps, risk assessment, urban planning, and policy-making. Combining data from different sensors, such as high-resolution multispectral images (HRI) and light detection and ranging (LiDAR) data, has shown great potential in building extraction. Deep learning (DL) is increasingly used in multi-modal data fusion and urban object extraction. However, DL-based multi-modal fusion networks may under-perform due to insufficient learning of “joint features” from multiple sources and oversimplified approaches to fusing multi-modal features. Recently, a hybrid attention-aware fusion network (HAFNet) has been proposed for building extraction from a dataset, including co-located Very-High-Resolution (VHR) optical images and light detection and ranging (LiDAR) joint data. The system reported good performances thanks to the adaptivity of the attention mechanism to the features of the information content of the three streams but suffered from model over-parametrization, which inevitably leads to long training times and heavy computational load. In this paper, the authors propose a restructuring of the scheme, which involved replacing VGG-16-like encoders with the recently proposed EfficientNet, whose advantages counteract exactly the issues found with the HAFNet scheme. The novel configuration was tested on multiple benchmark datasets, reporting great improvements in terms of processing times, and also in terms of accuracy. The new scheme, called HAFNetE (HAFNet with EfficientNet integration), appears indeed capable of achieving good results with less parameters, translating into better computational efficiency. Based on these findings, we can conclude that, given the current advancements in single-thread schemes, the classical multi-thread HAFNet scheme could be effectively transformed by the HAFNetE scheme by replacing VGG-16 with EfficientNet blocks on each single thread. The remarkable reduction achieved in computational requirements moves the system one step closer to on-board implementation in a possible, future “urban mapping” satellite constellation.


2020 ◽  
pp. neurintsurg-2020-017053
Author(s):  
Emanuele Orru' ◽  
Miklos Marosfoi ◽  
Neil V Patel ◽  
Alexander L Coon ◽  
Christoph Wald ◽  
...  

BackgroundExisting travel restrictions limit the mobility of proctors, significantly delaying clinical trials and the introduction of new neurointerventional devices. We aim to describe in detail technical and legal considerations regarding international teleproctoring, a tool that could waive the need for in-person supervision during procedures.MethodsInternational teleproctoring was chosen to provide remote supervision during the first three intracranial aneurysm treatments with a new flow diverter (currently subject of a clinical trial) in the US. Real-time, high-resolution transmission software streamed audiovisual data to a proctor located in Canada. The software allowed the transmission of images in a de-identified, HIPAA-compliant manner.ResultsAll three flow diverters were implanted as desired by operator and proctor and without complication. The proctor could swap between images from multiple sources and reported complete spatial and situational awareness, without any significant lag or delay in communication. Procedural times and radiologic dose were similar to those of uncomplicated, routine flow diversion cases at our institution.ConclusionsInternational teleproctoring was successfully implemented in our clinical practice. Its first use provided important insights for establishing this tool in our field. With no clear horizon for lifting the current travel restrictions, teleproctoring has the potential to remove the need for proctor presence in the angiography suite, thereby allowing the field to advance through the continuation of trials and the introduction of new devices in clinical practice. In order for this tool to be used safely and effectively, highly reliable connection and high-resolution equipment is necessary, and multiple legal nuances have to be considered.


2017 ◽  
Vol 23 (2) ◽  
pp. 366-375 ◽  
Author(s):  
Jonathan M. Hyde ◽  
Gérald DaCosta ◽  
Constantinos Hatzoglou ◽  
Hannah Weekes ◽  
Bertrand Radiguet ◽  
...  

AbstractIrradiation of reactor pressure vessel (RPV) steels causes the formation of nanoscale microstructural features (termed radiation damage), which affect the mechanical properties of the vessel. A key tool for characterizing these nanoscale features is atom probe tomography (APT), due to its high spatial resolution and the ability to identify different chemical species in three dimensions. Microstructural observations using APT can underpin development of a mechanistic understanding of defect formation. However, with atom probe analyses there are currently multiple methods for analyzing the data. This can result in inconsistencies between results obtained from different researchers and unnecessary scatter when combining data from multiple sources. This makes interpretation of results more complex and calibration of radiation damage models challenging. In this work simulations of a range of different microstructures are used to directly compare different cluster analysis algorithms and identify their strengths and weaknesses.


2000 ◽  
Vol 647 ◽  
Author(s):  
S.W.H. Eijt ◽  
C.V. Falub ◽  
A. van Veen ◽  
H. Schut ◽  
P.E. Mijnarends ◽  
...  

AbstractThe formation of nanovoids in Si(100) and MgO(100) by 3He ion implantation has been studied. Contrary to Si in which the voids are generally almost spherical, in MgO nearly perfectly rectangular nanosize voids are created. Recently, the 2D-ACAR setup at the Delft Positron Research Center has been coupled to the intense reactor-based variable-energy positron beam POSH. This allows a new method of monitoring thin layers containing nanovoids or defects by depth-selective high-resolution positron beam analysis. The 2D-ACAR spectra of Si with a buried layer of nanocavities reveal the presence of two additional components, the first related to para-positronium (p-Ps) formation in the nanovoids, and a second one most likely related to unsaturated Si-bonds at the internal surface of the voids. The positronium is present in excited kinetic states with an average energy of 0.3 eV. Refilling of the cavities by means of low dose 3He implantation (1×1014 cm−2) followed by annealing reduces the formation of Ps and the width of the Ps peak in the ACAR spectrum. This width reduction is due to collisions of Ps with He atoms in the voids. In MgO, p-Ps formed with an initial energy of ~3 eV shows a final average energy of 1.6 eV at annihilation due to collisions with the cavity walls. Possibilities of this new, non-destructive method of monitoring the sizes of cavities and the evolution of nanovoid layers will be discussed.


Polymers ◽  
2021 ◽  
Vol 13 (17) ◽  
pp. 2973
Author(s):  
Rory Gibney ◽  
Jennifer Patterson ◽  
Eleonora Ferraris

The development of commercial collagen inks for extrusion-based bioprinting has increased the amount of research on pure collagen bioprinting, i.e., collagen inks not mixed with gelatin, alginate, or other more common biomaterial inks. New printing techniques have also improved the resolution achievable with pure collagen bioprinting. However, the resultant collagen constructs still appear too weak to replicate dense collagenous tissues, such as the cornea. This work aims to demonstrate the first reported case of bioprinted recombinant collagen films with suitable optical and mechanical properties for corneal tissue engineering. The printing technology used, aerosol jet® printing (AJP), is a high-resolution printing method normally used to deposit conductive inks for electronic printing. In this work, AJP was employed to deposit recombinant human collagen type III (RHCIII) in overlapping continuous lines of 60 µm to form thin layers. Layers were repeated up to 764 times to result in a construct that was considered a few hundred microns thick when swollen. Samples were subsequently neutralised and crosslinked using EDC:NHS crosslinking. Nanoindentation and absorbance measurements were conducted, and the results show that the AJP-deposited RHCIII samples possess suitable mechanical and optical properties for corneal tissue engineering: an average effective elastic modulus of 506 ± 173 kPa and transparency ≥87% at all visible wavelengths. Circular dichroism showed that there was some loss of helicity of the collagen due to aerosolisation. SDS-PAGE and pepsin digestion were used to show that while some collagen is degraded due to aerosolisation, it remains an inaccessible substrate for pepsin cleavage.


2021 ◽  
Author(s):  
◽  
Muhammad Ali Raza Anjum

<p>Nuclear Magnetic Resonance spectroscopy (NMR) is a powerful technique for rapid and efficient quantitation of compounds in chemical samples. NMR causes the nuclei in the molecules to resonate and various chemical arrangements appear as peaks in the Fourier spectrum of a free induction decay (FID). The spectral parameters elicited from the peaks serve as a fingerprint of the chemical components contained in the molecule. These fingerprints can be employed to understand the chemical structure.  Signal acquired from a NMR spectrometer is ideally modelled as a superposition of multiple damped complex exponentials (cisoids) in Additive White Gaussian Noise (AWGN). The number as well as the spectral parameters of the cisoids need to be estimated for characterisation of the underlying chemicals. The estimation, however, suffers from numerous difficulties in practice. These include: unknown number of cisoids, large signal length, large dynamic range, large peak density, and numerous distortions caused by experimental artefacts.  This thesis aims at the development of estimators that, in view of the above-mentioned practical features, are capable of rapid, high-resolution and apriori-information-free quantitation of NMR signals. Moreover, for the analytic evaluation of the performance of such estimators, the thesis aims to derive interpretable analytic results for the fundamental estimation theory tool for assessing the performance of an unbiased estimator: the Cramer Rao Lower Bound (CRLB). By such results, we mean those that analytically allow the determination, in terms of the CRLB, of the impact of the free model parameters on the estimator performance.  For the CRLB, we report analytic expressions on the variance of unbiased parameter estimates of damping factors, frequencies and complex amplitudes of an arbitrary number of damped cisoids embedded in AWGN. In addition to the CRLB, analytic expressions for the determinant and the condition number of the associated Fisher Information Matrix (FIM) are also reported. Further results, in similar order, are reported for two special cases of the damped cisosid model: the Magnetic Resonance Relaxometry model and the amplitude-only model (employed in quantitative NMR - qNMR). Some auxiliary results for the above-mentioned models are also presented, i.e., on the multiplicity of the eigenvalues and the factorisation of the characteristic polynomial associated with their respective FIMs.  These results have not been previously reported. The reported theoretical results successfully account for various physical and chemical phenomena observed in experimental NMR data, and quantify their impact on the accuracy of an unbiased estimator as a function of both model and experimental parameters, e.g., influence of prior knowledge, peak multiplicity, multiplet symmetry, solvent peak, carbon satellites, etc.  For rapid, high-resolution and apriori-information-free quantitation of NMR signals, a sub-band Steiglitz-McBride algorithm is reported. The developed algorithm directly converts the time-domain FID data into a table of estimated amplitudes, phases, frequencies and damping factors, without requiring any previous knowledge or pre-processing. A 2D sub-band Steiglitz-McBride algorithm, for the quantitation of 2D NMR data in a similar manner, is also reported. The performance of the developed algorithms is validated by their application to experimental data, which manifests that they outperform the state-of-the-art in terms of speed, resolution and apriori-information-free operation.</p>


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