Acoustic Volume Research Articles

Using the hydroacoustic and mini trawl data for estimating fish density in the eastern part of Banyuasin coastal waters, South Sumatra of Indonesia

The hydroacoustic and mini trawl sampling was conducted to estimate a distribution pattern of fish density in the eastern part of Banyuasin coastal waters, South Sumatra, Indonesia. These surveys were carried out in September 2017 using a SIMRAD EK15 single‐beam echo sounder with a 200 kHz operating frequency. Catch data obtained from the mini bottom trawl were used to examine a dominant species for refining the TS value concerning the fish density estimation along the hydroacoustic track. The ponyfishes (Eubleekeria jonesi) from the Leiognathidae family were found at each station with the highest relative abundance (50.98%). Hence this species was used to refine target strength values for estimating the acoustic volume density. These volume densities of 206 ESDU ranged from 0 to 9048 fish 1000m–3, with an average of 930 fish 1000m–3. The results also described a distribution pattern of fish densities hence this information could be valuable to the fishery manager for improving sustainable management approaches.

MP30-12 VALIDATION OF MOBILE APPLICATION MEASURING VOIDED VOLUME: A PILOT PROSPECTIVE STUDY

You have accessJournal of UrologyCME1 May 2022MP30-12 VALIDATION OF MOBILE APPLICATION MEASURING VOIDED VOLUME: A PILOT PROSPECTIVE STUDY Hwanik Kim, Jin Hyuck Kim, Changhee Ye, Gyoohwan Jung, Jung Kwon Kim, Hakmin Lee, Seong Jin Jeong, and Sangchul Lee Hwanik KimHwanik Kim More articles by this author , Jin Hyuck KimJin Hyuck Kim More articles by this author , Changhee YeChanghee Ye More articles by this author , Gyoohwan JungGyoohwan Jung More articles by this author , Jung Kwon KimJung Kwon Kim More articles by this author , Hakmin LeeHakmin Lee More articles by this author , Seong Jin JeongSeong Jin Jeong More articles by this author , and Sangchul LeeSangchul Lee More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002573.12AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Comparing urine flow tests performed at the clinic with the actual urination at home, there can be a mental burden and straining of urine that can affect the test results. The need for a comfortable, convenient, and even portable, home-based device has led to the development of novel uroflowmetry technology. This study aimed to evaluate the accuracy and reliability of a new smartphone-based acoustic voiding volume measurement application compared to conventional ultrasound bladder volume scanner. METHODS: A total of 12 subjects from September 2020 to March 2021 were prospectively enrolled with informed consent to compare novel acoustic voiding volume measurement to conventional ultrasound bladder volume scanner. 2 subjects were excluded their measurement do not meet our standard of sound quality (i.e. voiding in environment with very loud fan noise, voiding to the wall, door slams). Finally, 10 patients with 50 voiding measurements were included for analysis. The value measured before urination by bladder scanner (A), the value measured after urination by bladder scanner (B), and the value of voided volume measured by smartphone-based acoustic voiding volume measurement mobile application (C) were compared between the 2 techniques. Reliability and accuracy of the voided volume results were compared using Pearson correlation coefficient, and student t-test, respectively. RESULTS: 10 healthy volunteers were included in the study. Median age was 53.5. Median values of uroflowmetry proflile are as follows: Qmax: 16.3mL/s, Voided volume: 256.8mL, and postvoid residual urine: 7.5mL. Voided volume between the 2 techniques revealed strong visual correlation (r=0.71, p=0.02). When compared to conventional uroflowmetry. When analyzed separately for each individual, each participant showed stronger correlation (range: 0 59-1.00). CONCLUSIONS: The acoustic voiding volume measurement application can take over the role of traditional bladder scan resulted from our validation. Through comparison of bladder scan measurements before and after urination, it was confirmed that the urine volume measurement using the smartphone PRIVY application was accurate. PRIVY application can be a breakthrough that can lower the barriers to entry to health management of patients' urination. Further large-scale studies will further increase the credibility of our results. Source of Funding: N/A © 2022 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 207Issue Supplement 5May 2022Page: e482 Advertisement Copyright & Permissions© 2022 by American Urological Association Education and Research, Inc.MetricsAuthor Information Hwanik Kim More articles by this author Jin Hyuck Kim More articles by this author Changhee Ye More articles by this author Gyoohwan Jung More articles by this author Jung Kwon Kim More articles by this author Hakmin Lee More articles by this author Seong Jin Jeong More articles by this author Sangchul Lee More articles by this author Expand All Advertisement PDF DownloadLoading ...

Seismic inversion as a reliable technique to anticipating of porosity and facies delineation, a case study on Asmari Formation in Hendijan field, southwest part of Iran

Porosity and facies are two main properties of rock which control the reservoir quality and have significant role in petroleum exploration and production. Well and seismic data are the most prevalent information for reservoir characterization. Well information such as logs prepare adequate vertical resolution but leave a large distance between the wells. In comparison, three-dimensional seismic data can prepare more detailed reservoir characterization in the inter-well space. Generally, seismic data are an efficient tool for identification of reservoir structure; however, such data usable in reservoir characterization. Therefore, these two types of information were incorporated in order to obtain reservoir properties including porosity and facies in the study area. Using Multimin algorithm, petrophysical analysis was carried out for estimation of reservoir porosity. Then, an accurate post-stack inversion was accomplished to obtain the acoustic impedance volume. The results showed that the Ghar sandstone is characterized by a lower acoustic impedance compared to the high acoustic impedance Asmari Formation. Because of a relationship between acoustic impedance and reservoir properties (i.e., porosity), porosity cube calculation was performed by artificial neural network method which is a popular approach for parameter estimation in petroleum exploration. The consequences showed a good agreement between log based and seismic inversion-derived porosity. The inversion results and well logs cross-plots analyses illustrated that the Ghar member considered as a high quality zone with porosity 22 to 32 percent and the Asmari dolomite shows a low quality interval characters with porosity 1 to 6 percent. The findings of this study can help for better understanding of reservoir quality (especially porous Ghar member delineation) by lithology discrimination in the analysis of identification reservoirs and finding productive well location in Hendijan field.

Rethinking Igor Stravinsky historically and theoretically — III

The article is a continuation of the author’s reflections on the phenomenon of musical polymorphism (the beginning is in Vol. 124, 2019; the continuation is in Vol. 128, 2020). Stravinsky’s use of the environment, space, motion, dissonance, and Janus morphemes is considered as his inheritance from a tradition dating back to the work of his great predecessors. The musical tableau Sadko by RimskyKorsakov, the introduction Dawn on the Moscow River to Mussorgsky’s Khovanshchina, and Borodin’s symphonic poem In the Steppes of Central Asia are a clear confirmation of this. In Sadko Rimsky-Korsakov reveals himself as the founder of musical polymorphism. The multi-element polymorphism of Mussorgsky’s Dawn on the Moscow River forms the basis of the first tableau in Stravinsky’s Petrushka. In the Steppes of Central Asia is an example of a multi-elemental, polymorphic structure, recreated outside an existing object: a native caravan crossing the desert, guarded by a Russian military detachment. Its stereophonic nature appears in the displacement of the textural elements to the rear and the foreground, their spatial compression or expansion, changes to the acoustic volume, sound coloration. Introductory violins octave unison in In the Steppes of Central Asia displays its hidden timbre-polyphonic nature. In the historical perspective, this compositional discovery by Borodin foreshadows a similar approach in Stravinsky’s musical language. The timbrical layering of the unison can be traced in Dances of the Young Girls from The Rite of Spring, The Lullaby in the Storm from The Fairy’s Kiss. The rhythmic ostinato features of Rimsky-Korsakov’s and Borodin’s scores are developed by Stravinsky to the elaborated part of his musical language. The structures with more or less constant, exact repetitions are used in The Rite of Spring, Three Tales for Children, Three Pieces for String Quartet, The Soldier’s Tale, The Wedding, Symphony of Psalms.

Optimization of seismic-guided 3-D marine magnetotelluric imaging in a complex fold-thrust belt setting in NW Borneo, Malaysia

SUMMARY The use of seismic-derived structure tensor to guide the inversion of non-seismic data has been gaining increasing attention because of its ability to constrain the inversion result to honour structural information from seismic reflectivity. While the cross-gradient method has been recently adapted to this problem, there is a need to further examine how the choice of the various regularization weighting factors and the design of the starting model impact the image-guided results. In this paper focused on marine magnetotellurics (MT), we study several practical aspects of seismic-guided electromagnetic (EM) inversion to see on what can be improved from the current practice. We then show practical examples of how the cross-gradient method can be applied to get a more geologically pleasing model that fits the data. We also show that there are subjective choices in how to effectively apply the method. First, using a field-realistic synthetic model, we established what would be the suitable regularization weights in the vertical and horizontal directions. Secondly, for the actual 3-D survey data, we compared the use of structure tensors derived from anisotropic pre-stack depth migration (APSDM) reflectivity, high-fidelity full-waveform inversion (FWI) velocity and acoustic impedance inversion volumes to guide cross-gradient anisotropic resistivity inversion with initial half-space resistivity starting models. We determined post-facto the optimum structure tensor weights using well logs as the ground truth. We found that the initial model built using horizon-based interpolated resistivity logs from multiple wells in the anisotropic inversion guided with seismic FWI velocity gave the best match to well logs as compared to the other options. However, given that resistivity logs from multiple wells may not always be available for a robust initial model construction in frontier exploration, we suggest that the structure tensor from APSDM reflectivity data is still preferred since the APSDM reflectivity data have well-defined structural information.

Finite-amplitude sound propagation effects in volume backscattering measurements for fish abundance estimation

Scientific advice for governmental management of marine resources relies on acoustical observation methods. Quantification and identification of fish and plankton species are often achieved using multi-frequency acoustic data. Accurate measurements of backscattering cross-sections and volume backscattering coefficients are essential. Systematic errors from finite-amplitude sound propagation are demonstrated in experimental survey measurements on Atlantic mackerel using 120 kHz and 200 kHz echosounders and high power settings. Finite-amplitude signal distortion causes excess transmission loss that is not accounted for in fisheries acoustics today, other than by fixed limits on the maximum transmitted power. The demonstrated errors are of a magnitude that can seriously bias abundance estimation and species identification. It is shown how the finite-amplitude effects can be modelled and predicted quantitatively, within a framework of electroacoustic power budget equations. A method is provided to calculate related errors in echosounder calibration and oceanic measurement of acoustic volume backscattering. When accounting for finite-amplitude effects in echosounder signal processing, higher transmit powers can be used when needed to improve signal-to-noise ratio or extend measurement range. The results indicate that historical survey data can be adjusted for such errors using numerical simulations. The echosounder characteristics relevant to finite-amplitude effects can be determined by laboratory measurements.

Target density estimation of mesopelagic fish using a towed, broadband, split-beam, acoustic scattering system

The ocean mesopelagic zone (200–1000 m) features a complex temporal and spatial distribution of organisms which may play an important role in ocean biogeochemical cycles. Yet a quantitative account of the abundance, biomass and migration behaviors of mesopelagic inhabitants is still lacking. Shipboard echosounders are limited by acoustic attenuation at higher frequencies constraining the usable frequency band for investigating deep sound scattering layers, as well as large acoustic sampling volumes, a result of the large depths associated with the deep scattering layers, combined with the inherent complexity of mesopelagic communities. Deep-See, a towed platform carrying multiple broadband sonars, focuses on individual targets in the deep scattering layers, to help interpret shipboard data. Target density estimation is the first step towards determining biomass in the mesopelagic zone. Two methods are investigated and applied to a summer 2019 dataset collected using two broadband split-beam echosounders (5.5–18.5 kHz, 18–47 kHz) on Deep-See in the slope waters off the New England Continental Shelf. The echo-counting method utilizes echo magnitude and phase information to determine singe targets while echo-statistics involves comparison of data to a physics-based numerical simulation to predict the statistics of broadband echoes from which target density can be extracted.

Proton dosimetry using superheated droplets: Quantification with ultrasound

Superheated nanodroplets were proposed for dosimetry in proton therapy. Proton energy deposition within the droplet core leads to droplet vaporization. Vaporizations can be localized through acoustic pulse-echo, and used to measure the proton stopping distribution. Since protons can only lead to vaporizations as they stop, the probability of vaporization is estimated as the probability of a proton stopping within a droplet. Assuming that the number of vaporizations follows a binomial distribution, conversion from vaporizations to number of protons requires knowledge of: droplet size distribution and concentration, and acoustic FoV volume. Here we address the latter. We propose an experimental and numerical method to characterize the 2-way acoustic elevational width of a linear array. First, the impulse response and 1-way field of the acoustic array was measured using a hydrophone. Then, the 1-way field was fitted to field-ii simulations using a least-squares algorithm to estimate the optimal parameters. Finally, the 2-way acoustic field was simulated. The effective elevational width depends on the scattering cross section of the resulting microbubbles, and was determined from the experimental range of backscattering intensities. The method allowed to predict the vaporization counts of experimental measurements where three different size-sorted droplet populations were used.

Sand production prediction of deep gas wells in Bashijiqike Formation of the Keshen block

In order to effectively prevent the occurrence of sand production during the gas well production, rock mechanics tests were carried out for a deep tight sandstone gas reservoir in Bashijiqike Formation of the Keshen blockk, and the logging prediction models of mechanics parameters were established. At the same time, considering the effect of reservoir pressure and stimulation measures, based on the analysis of stress state of borehole wall and using M-C criterion, the calculation model of the critical production pressure of gas well was established to achieve the purpose of guiding production and improving the gas well production. The results show that the relationship between rock mechanic parameters with acoustic wave and volume density of the Bashijiqike Formation reservoir was studied, and the response mechanism of rock mechanics parameters was revealed, thus the logging calculation model of rock mechanics parameters was established. Based on the drilled fracturing and logging data, the multi-parameter prediction method of the formation pore pressure and the in-situ stress calculation model were established. The critical production pressure has also been significantly reduced, and the risk of sand production in gas wells increased significantly. After water immersion and acid fracturing, the compressive and elastic modulus of the rock samples decreased obviously, and the maximum decrease of the critical production pressure of the reservoirs in the study area reached 9 MPa. In order to ensure the safe production, it is necessary to supplement formation energy or take more effective sand control measures in the study area. The research results can provide guiding significance for gas well production allocation in this area.

High-Sustained Concentrations of Organisms at Very low Oxygen Concentration Indicated by Acoustic Profiles in the Oxygen Deficit Region Off Peru

The oxygen deficient mesopelagic layer (ODL) off Peru has concentrations below 5 μmol O2 kg–1 and is delimited by a shallow upper oxycline with strong vertical gradient and a more gradual lower oxycline (lOx). Some regions show a narrow band of slightly increased oxygen concentrations within the ODL, an intermediate oxygen layer (iO2). CTD, oxygen and lowered Acoustic Doppler Current Profiler (LADCP, 300 kHz) profiles were taken on the shelf edge and outside down to mostly 2000 m. We evaluate here the acoustic volume backscatter strength of the LADCP signal representing organisms of about 5 mm size. Dominant features of the backscatter profiles were a minimum backscatter strength within the ODL, and just below the lOx a marked backscatter increase reaching a maximum at less than 3.0 μmol O2 kg–1. Below this maximum, the acoustic backscatter strength gradually decreased down to 1000 m below the lOx. The backscatter strength also increased at the iO2 in parallel to the oxygen concentration perturbations marking the iO2. These stable backscatter features were independent of the time of day and the organisms represented by the backscatter had to be adapted to live in this microaerobic environment. During daylight, these stable structures were overlapped by migrating backscatter peaks. Outstanding features of the stable backscatter were that at very low oxygen concentrations, the volume backscatter was linearly related to the oxygen concentration, reaching half peak maximum at less than 2.0 μmol O2 kg–1 below the lOx, and the depth-integrated backscatter of the peak below the lOx was higher than the integral above the Ox. Both features suggest that sufficient organic material produced at the surface reaches to below the ODL to sustain the major fraction of the volume backscatter-producing organisms in the water column. These organisms are adapted to the microaerobic environment so they can position themselves close to the lower oxycline to take advantage of the organic particles sinking out of the ODL.

Reservoir properties modelling using multi-attribute seismic analysis in south Sumatra basin, Indonesia

Seismic inversion and multi-attribute analysis method are used in this research to characterize the reservoir properties. Where both of these methods will be resulted an acoustic impedance volume and log property volumes. The property log volumes were created from density, porosity, Gamma-Ray (GR) and Water Saturation (Sw) log. There are 4 wells that are used in this research, they are EM-31, EM-32, EM-33 and EM-34 and a 3D seismic data post-stack time migration. Based on a map of acoustic impedance distribution, the reservoir target has an acoustic impedance value of 6.000 ((m/s)*(g/cc)) to 8.000 ((m/s)*(g/cc)). Furthermore, based on the map of the distribution of the log property, the reservoir has a density value with a range of 2.3 g/cc up to 2.4 g/cc, porosity value > 10%, the GR value of less than 100 API and Sw 50% to 55%. Thus, it can be concluded that reservoir has a lithology of sandstones, has a fairly good porosity and contains oil fluids.

Reaction front development from ignition spots in n-heptane/air mixtures: Low-temperature chemistry effects induced by ultrafine water droplet evaporation

Effects of low-temperature chemistry induced by ultrafine water droplet evaporation on reaction front development from an ignition spot with temperature gradient are studied in this work. The Eulerian–Eulerian method is used to simulate the gas–liquid two-phase reactive flows, and the physical model is one-dimensional spherical reactor with stoichiometric gaseous n-heptane/air mixture and ultrafine monodisperse water droplets (initial diameter 5 μm). Homogeneous ignitions of two-phase mixtures are first simulated. The water droplets can completely evaporate in the reactor prior to ignition, and hence pronouncedly reduce gas temperature, which may induce the low-chemistry reactions. It is found that the turnover temperature for negative temperature coefficient range increases with droplet volume fraction. Three-stage ignitions are present when the volume fraction is beyond a critical value, that is, low-temperature, intermediate-temperature, and high-temperature ignitions. The chemical explosive mode analysis also confirms the low-chemistry reactions induced by the evaporation of ultrafine water droplets. Then, reaction front development from an ignition spot with temperature gradient in two-phase mixtures is analyzed based on one-dimensional simulations. Different modes for reaction front origin in the spot are identified, based on the initial gas temperature and lower turnover temperature. Specifically, the reaction front can be initiated at the left and right ends of the ignition spot, and inside it. Detailed reaction front developments corresponding to the above three modes are discussed. In addition, the pressure wave from high-temperature ignition is important, compared to those from low and intermediate chemistries. The reaction front propagation speed and thermal states of fluid particles corresponding to different reaction front initiation modes are analyzed. Moreover, autoignition modes are summarized in the diagrams of normalized temperature gradient vs normal acoustic time and droplet volume fraction. The detonation limits of two-phase mixtures highly depend on the droplet volume fraction and are not regularly peninsular-shaped, like those for purely gaseous mixtures.

Reservoir properties prediction using seismic inversion and geostatistical integration

Exploration and production in the sand reservoir still have their challenges due to the low porosity and permeability characteristics. This study was conducted to analyse the characteristics of a tight sand reservoir based on a log property distribution map, using acoustic impedance inversion and multi-attribute analysis. Stepwise regression multi-attribute analysis is a method that uses the best attributes to predict the target log by going through a trial and error process. Choosing the right seismic attributes can provide a better depiction of the target zone. This research was conducted to obtain a map of subsurface geological structures, acoustic impedance volumes. Then, we performed a multi-attribute analysis to obtain a prediction of volume log properties such as pseudo gamma-ray, density and porosity using the stepwise regression method. The results of acoustic impedance seismic inversion and stepwise regression multi-attribute analysis shows that the reservoir is a gas with tight sand lithology, which has a range of acoustic impedance values of 15,000 ((ft/s)*(g/cc)) up to 30,000 ((ft/s)*(g/cc)), porosity of 12% to 24%, and the distribution of Sw of 8-13%. The density and porosity maps obtained from the multi-attributes analysis can help in the long-term exploration and production stages. Its aims are to improve primary recovery and tertiary recovery, understanding the stratigraphic traps, and continuity of reservoir layers.

Characterization of Thin Gas Hydrate Reservoir in Ulleung Basin with Stepwise Seismic Inversion

Natural gas hydrates (GHs) filling sand layer pores are the most promising GHs that can be produced via conventional mechanisms in deep-sea environments. However, the seismic tracking of such thin GH-bearing sand layers is subject to certain limitations. For example, because most GH-bearing sand layers are thin and sparsely interbedded with mud layers, conventional seismic data with a maximum resolution of ~10 m are of limited use for describing their spatial distribution. The 2010 Ulleung Basin drilling expedition identified a relatively good GH reservoir at the UBGH2-6 site. However, the individual GH-bearing sand layers at this site are thin and cannot therefore be reliably tracked using conventional seismic techniques. This study presents a new thin layer tracking method using stepwise seismic inversion and 3D seismic datasets with two different resolutions. The high-resolution acoustic impedance volume obtained is then used to trace thin layers that cannot be harnessed with conventional methods. Moreover, we estimate the high-resolution regional GH distribution based on GH saturation derived from acoustic impedance at UBGH2-6. The thin GH layers, previously viewed as a single layer because of limited resolution, are further subdivided, traced, and characterized in terms of lateral variation.

Karakterisasi reservoir menggunakan metode Seismik Inversi Acoustic Impedance (AI) dan Seismik Multiatribut dengan Probabilistic Neural Network (PNN) pada lapangan Blok F3, North Sea Netherland

A 3D seismic acquisition has been carried out for oil and gas exploration in F3 field block of North Sea sector of the Netherland formed between the Jurassic and Cretaceous periods. The presence of hydrocarbons is indicated by the phenomenon of bright spots and gas chimneys below the surface. The data used are 3D post stack time migration seismic data and four wells with well log, checkshot and marker data availability. This study uses two methods in determining reservoir zones, namely the acoustic impedance inversion method and the multi-attribute method with PNN. Both methods integrate seismic data with well data. AI inversion method is used to predict the physical properties of rocks, namely their acoustic impedance values. The multi-attribute method is used to predict well log properties from seismic data. Non-linear multi-attribute transformation is obtained by the process of training neural networks with a type of probabilistic neural network (PNN). In this research, acoustic impedance volume and porosity estimation volume will be made to identify the hydrocarbon reservoir prospect zone. The two methods are then applied to the Netherlands F3 seismic field data, and the results show that there are three sandstone reservoir zones that have an acoustic impedance range between 4100-4800 (m/s)*(gr/cc) and porosity range between 29-35 (% ).

Study of factors determining the amplitude-frequency characteristics of acoustic noise in well logging

The article considers the factors that affect the spectral characteristics of acoustic noise recorded in active horizontal wells during logging. Based on the results of physical experiments performed on well models, the presence of resonance phenomena in the acoustic volume of the wellbore, the influence of the location of sensor and the tool body on the measurement result under identical conditions, the need to calibrate downhole tools for bringing their characteristics to a single scale are shown.

Analyses of Peace River Shallow Water Ice Profiling Sonar data and their implications for the roles played by frazil ice and in situ anchor ice growth in a freezing river

Abstract. Peace River SWIPS (Shallow Water Ice Profiling Sonar) data were analyzed to quantify the roles of frazil ice and riverbed anchor ice grown in situ during the initial buildup of a seasonal ice cover. Data were derived through quasi-continuous monitoring of frazil parameters throughout the water column, providing direct and indirect measures of anchor ice volume and mass growth rates. Analyses utilized water level and air and water temperature information in conjunction with acoustic volume backscattering coefficient data to track and interpret spatial and temporal changes in riverbed and water column ice. Interest focused on four frazil intervals characterized by anomalously low levels of frazil content (relative to simulations with an anchor-ice-free river ice model) as distinguished by two strikingly different types of time dependences. A simple physical model was proposed to quantitatively account for discrepancies between measured and simulated results in terms of the pronounced dominance of anchor ice as an initial source of river ice volume and mass. The distinctive differences in temporally variable water column frazil content are attributed, in this model, to corresponding differences in the stabilities of riverbed anchor ice layers against detachment and buoyancy-driven movement to the river surface. In accord with earlier observations, the stability of in situ grown riverbed ice layers appears to be inversely proportional to cooling rates. The strength of the coupling between the two studied ice species was shown to be strong enough to detect changes in the anchor ice constituent from variations in water column frazil content.

Facies probability application for gas reservoir characterization

Reservoir characterization through seismic inversion is the principle method in hydrocarbon exploration. Facies probability is an advance method of reservoir characterization which integrates model-based seismic inversion and facies classification to construct a better reservoir modelling. The reservoir modelling is produced from four main steps. First is crossplot analysis to define the relation between acoustic parameter and petrophysics parameter. Second, model-based seismic inversion to produce acoustic impedance volume from seismic data. Third, facies classification which is defined from porosity effective, shale volume and water saturation. Final step is Bayesian Inference Framework to model probability density function (pdf) of each facies. The result of crossplot analysis shows that there is a linear relationship between acoustic impedance and porosity hence the porosity volume can be derived from the model-based inversion result. Facies classification is divided into two categorical zone, pay and non-pay. Pay zone is categorized as a high porosity layer filled with gas. Its parameters fit with Vshale > 0.6, Sw < 0.7 and porosity effective > 0.22. Then estimation is run using Bayesian probability into acoustic impedance volume and porosity volume resulting probability volume of each facies.

Dolomitization geometry and reservoir quality from supervised Bayesian classification and probabilistic neural networks: Midland Basin Leonardian Wichita and Clear Fork Formations

Extensive dolomitization is prevalent in the platform and periplatform carbonates in the Lower-Middle Permian strata in the Midland and greater Permian Basin. Early workers have found that the platform and shelf-top carbonates were dolomitized, whereas slope and basinal carbonates remained calcitic, proposing a reflux dolomitization model as the possible diagenetic mechanism. More importantly, they underline that this dolomitization pattern controls the porosity and forms an updip seal. These studies are predominately conducted using well logs, cores, and outcrop analogs, and although exhibiting high resolution vertically, such determinations are laterally sparse. We have used supervised Bayesian classification and probabilistic neural networks (PNN) on a 3D seismic volume to create an estimation of the most probable distribution of dolomite and limestone within a subsurface 3D volume petrophysically constrained. Combining this lithologic information with porosity, we then illuminate the diagenetic effects on a seismic scale. We started our workflow by deriving lithology classifications from well-log crossplots of neutron porosity and acoustic impedance to determine the a priori proportions of the lithology and the probability density functions calculation for each lithology type. Then, we applied these probability distributions and a priori proportions to 3D seismic volumes of the acoustic impedance and predicted neutron porosity volume to create a lithology volume and probability volumes for each lithology type. The acoustic impedance volume was obtained by model-based poststack inversion, and the neutron porosity volume was obtained by the PNN. Our results best supported a regional reflux dolomitization model, in which the porosity is increasing from shelf to slope while the dolomitization is decreasing, but with sea-level forcing. With this study, we determined that diagenesis and the corresponding reservoir quality in these platforms and periplatform strata can be directly imaged and mapped on a seismic scale by quantitative seismic interpretation and supervised classification methods.

Automated detection of sigmatism using deep learning applied to multichannel speech signal

This paper presents a system for the analysis of acoustic data for the computer-aided diagnosis and therapy of sigmatism in children. The analysis is focused on the detection and recognition of selected articulation disorders in sibilant sounds. The system relies on the dedicated data acquisition device recording the speech signal using 15 microphones spatially arranged around the speaker's mouth. The collected speech corpus contains 923 samples of the /s/ and /ʃ/ consonants from 98 five- and six-year-old children with either normative or pathological pronunciation features. Each recording is supplemented with a detailed speech therapy annotation. A dedicated multibranch convolutional neural network architecture was designed for the speech sample classification. The filter bank energy feature maps are extracted from each channel along with their two derivatives in the time domain. The feature maps are aggregated along different dimensions to constitute a four-dimensional data structure called acoustic volume, being the input data for the deep network. We proposed three ways to aggregate the multichannel data into the acoustic volume and two techniques for the data augmentation to enlarge the available dataset and avoid overfitting. Classification experiments involving different data subsets have proven the system's ability to detect the analyzed pronunciation disorders with reasonable accuracy. The framework with speech data organized spatially in five channels provides the most efficient classification.