Produção Científica
Apresentação
| Evaluation of Static and Dynamic Elastic Properties in Carbonate Rock The understanding of rocks mechanical properties is essential for some of the petroleum industry sectors, such as drilling, well stimulation and development. Rock mechanics data, as Young's modulus and Poisson's ratio, can be obtained by the static and dynamic conditions using triaxial compressive and ultrasonic tests, respectively. This work analyses the behaviour of static and dynamic elastic properties in a set of 20 carbonate core samples and compares with other literature results. Our approach is based in fit equations to predict static properties from the dynamic data, considering the occurrence of the frictional sliding or closing of cracks and microcracks, while performing triaxial tests. The results indicated a strong relationship among the effective pressures applied, porosity, density, and the efficiency of static and dynamic property relations. Additionally, porosity type could be indicated as one of the causes of the difference between static and dynamic moduli, since the inclusion of density and porosity in the relations demonstrated a significant improvement between Young's static and dynamic modulus correlations. |
Apresentação
| Pressure Effects on the Prediction of the Dry Bulk Modulus Using the Nur Critical Porosity Model Carbonate reservoirs are some of the most important plays in the oil and gas business around the world. The monitoring of fluid distribution within those rocks is not an easy task due to the complexity of their pore structure, which also influences the relationship between the petrophysical properties and seismic data. Fluid substitution theories like Biot-Gassmann often used for that monitoring, depend on the accurate info of the dry bulk modulus (Kdry), which is usually obtained from P- and S-wave velocities. In cases where those velocities are not available, it is possible to use other theories like the Nur (critical porosity) model to estimate Kdry from porosity and mineral content. This work aims to use a dataset of petrophysical data measured in core plugs to evaluate how the external pressure influence the prediction of Kdry based on the Nur Model. The results indicated the impact of pressure in the lab measured porosity affect the accuracy of such predictions and a modification in the Nur Model is proposed for accounting those effects. |
Apresentação
| Correlation Between Hysteresis, Elastic Moduli and Petrophysical Properties in Sedimentary Rocks ut on 05 sandstones and 03 carbonate core samples. The results indicated that hysteresis is severely dependent on depositional texture, and it is directly related to Young modulus and Bulk modulus. Tight rocks exhibited higher hysteresis than friable rocks, due to frictional sliding and grain contact adhesion, which causes permanent damage to pore structure. Porosity displays an inverse relation to hysteresis, as high pore density enables rock’s matrix to deform and recover its shape without frictional sliding and grain contact adhesion. |
Apresentação
| Harvesting the computational power of heterogeneous clusters to accelerate seismic processing Cluster environments are crucial to modern geophysics. Major processing companies make use of one or more computational environments, whether they be in-house clusters or third-party public clouds, to guarantee the efficient execution of their processing flows. But the diversification of such environments created a demand for software tools that are able to scale with efficiency in these ever-increasing ecosystems. Aside from efficiency requirements, these tools must also be able to handle and recover automatically from the faults that arise from these new and complex ecosystems. In this paper, we discuss how we leverage the Scalable Partially Idempotent Tasks System (SPITS) programming model and the PY-PITS runtime system to efficiently harvest the computing power of heterogeneous systems in order to solve geophysics problems. We also present an experiment in which we combine the computational resources from several clusters and workstations simultaneously to perform the regularization of seismic data and demonstrate the scalability and robustness of the system. |
Apresentação
| Deep Structures Seismic Enhancement Using Singular Spectral Analysis in Time and Frequency Domain - Application in a ParnaÃba Basin Line – Brazil Land data seismic processing has always been a task of great challenge for industry, part because of statics problem and part because of the level of noise this kind of data usually has. In this paper we discuss the importance of a powerful filtering flow, designed for a special case scenario where there is a high level noise land data with duration of 20 seconds. We tested a recursive-iterative Singular Spectrum Analysis (RI-SSA) method, in time and frequency domain, on a subset of a regional transect seismic line of the ParnaÃba basin (Northeast of Brazil), with the idea of map deep structures from crust and interface crust-mantle. Since the structures of interest are between 8 and 15 seconds, only low frequency is desired. For this, we have applied the RI-SSA method along the time variable, to explore the correlation between the reflections, followed by the filtering, along the frequency variable, to explore the correlation between seismograms. The obtained results are very satisfactory. |
Apresentação
| Recursive-iterative Zero-phase Filtering via Singular Spectrum Analysis We present a recursive-iterative Singular Spectrum Analysis (RI-SSA) algorithm which explores the time-correlation between reflected events. The RI-SSA algorithm depends on the first eigenimage of the SVD of the data matrix only. It is formed by letting each column be the data vector shifted one place down. The first eigenimage is related to the part of the signal with most strong correlation along the time variable and may be transformed to a time signal, which mainly consists of the low-frequency part of the input signal. We show that this corresponds to filtering the data with a symmetric zero-phase filter, which is the autocorrelation of the first eigenvector associated to the time variable. The computational implementation may be done using the power-method in a recursive scheme, increasing the order of the data matrix, by increasing the number of shifted traces. This improves the separation of the input data in a low-frequency and high-frequency component. This separation may be further improved by adding iterations. The output of the RI-SSA algorithm is the low and high frequency part of the signal. We illustrate the effectiveness of this new approach to the prediction and subtraction of the ground-roll. |
Apresentação
| Evaluation of Borehole Effect of Mud Filtrate on Density Logging and a Brief Analysis of its Impact on Well-Seismic Tying The application of seismic data in reservoir characterization, direct hydrocarbon indication and production monitoring rely on the accuracy of elastic logs (Vásquez et al., 2004), which can be damaged by the mud filtrate invasion associated to the borehole condition. Corrections on density log sometimes are neglected, however, meaningful improvements on the correlation of the well to seismic tie can be achieved by performing proper rectifications. For this reason, in this paper we present a analysis of the impacts of borehole enlargement on the well-to-seismic tie based on density modelling and on a analysis of the caliper log. |
Apresentação
| Signal analysis and time-frequency representation using SSA and adaptive AR methods We apply the Singular Spectral Analysis (SSA) method in an iterative and recursive way to estimate individual components of the signal. Following we apply the short time autoregressive method to obtain a time-frequency representation of the signal. For the computing of the instantaneous frequency we provide a new equation which depend on a single autoregressive coefficient. The effectiveness of the new approach is demonstrated in a synthetic data example and in the removal of ground-roll noise from land seismic data. |
Apresentação
| Combining tilt derivative filters: new approaches to enhance magnetic anomalies We extend the concept of two earlier enhancement techniques based on the local phase of the magnetic anomaly, namely the vertical (TDR) and horizontal (TDX) tilt angles, which are defined by the inverse tangent of ratios involving the total horizontal gradient and the vertical derivative. These filters are useful to locate both shallow and deep sources, because they equalize the signal amplitudes. The proposed approach is based on the addition and subtraction of TDR and TDX. The TDR+TDX filter produces constant values over the causative bodies, while TDR-TDX generates peaks over the center of bodies and is constant out of them. By applying the proposed techniques to synthetic and aeromagnetic data we show that they locate more clearly the centers and edges of the sources in comparison to TDR and TDX, respectively. The combined filters have essentially the same computational cost as TDR and TDX and can replace them as auxiliary interpretation tools.Keywords: Qualitative Methods, Local Phase Filters, Aeromagnetic Data.RESUMO. Estendemos o conceito de duas técnicas de realce baseadas na fase local da anomalia magnética: as inclinações do sinal analÃtico (TDR) e do gradiente horizontal total (TDX), definidos pelo arco tangente de razões envolvendo o gradiente horizontal total e a derivada vertical. Estes filtros são úteis para localizar tanto fontes rasas quanto profundas. O método proposto baseia-se na adição e subtração dos filtros TDR e TDX. O filtro TDR+TDX produz valores constantes sobre as fontes causadoras, enquanto que o TDR-TDX produz picos sobre o centro dos corpos e é constante onde fontes causadoras não são verificadas. Aplicando as técnicas propostas aos dados sintéticos e reais mostra-se que elas localizam mais claramente os centros e as bordas dos corpos em comparação com o TDR e o TDX, respectivamente. Os filtros combinados têm essencialmente o mesmo custo computacional dos filtros originais, TDR e TDX, e podem substituÃ-los como ferramentas de interpretação.Palavras-chave: Métodos Qualitativos, Filtros de Fase Local, Dados Aeromagnéticos. Federal |
Apresentação
| 2D Poststack Seismic Data Inversion with Curvelet Denoising Preconditioning Seismic inversion methods are highly sensitive to the noise present in the data set. The need to enhance the signal-to-noise ratio (SNR) motivates the researchers do develop increasingly sophisticated denoising methods and combine them into other techniques. While some methodologies operate on a single scale, the curvelet transform established itself as multi-scale transform useful to decompose the seismic signals into multi-resolution elements. In this study, we evaluate the benefits of curvelet denoising as a preconditioning method to poststack seismic data in an 2D acoustic inversion processing using a Bayesian framework. Our tests on a synthetic data set modelled from the Marmousi model and the real data set from the Brazilian offshore Campos Basin have shown that the curvelet thresholding method can be successfully applied for random noise elimination. Even the use of a hard global threshold might allow improvements in the deepest parts. Future work will have to show whether alternatives that ensure a more robust way of selecting the coefficients can take into account the wavelength change with depth variation. |
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