scholarly journals A local binary patterns/variance operator based on guided filtering for seismic fault detection

2021 ◽  
Vol 3 (12) ◽  
Author(s):  
Renfei Tian ◽  
Xue Lei ◽  
Min Ouyang
Keyword(s):  
Fault Detection ◽  
Seismic Data ◽  
Oil And Gas ◽  
Local Binary Patterns ◽  
Identification Accuracy ◽  
Practical Significance ◽  
Noise Interference ◽  
Oil And Gas Exploration ◽  
Seismic Fault ◽  
Guided Filtering

AbstractAiming at suppressing noise interference, improving the fault detection ability of seismic data, fully excavating the effective information in seismic data, and further improving the accuracy of fault detection, this study proposes a seismic fault detection method that combines the local binary pattern/variance (LBP/VAR) operator with guided filtering. The proposed method combines the advantages of LBP/VAR and guided filtering to remove noise from seismic data, and can simultaneously smooth the data and preserve linear features. When compared with several existing methods (coherent operator, LBP/VAR operator, LBP/VAR operator based on median filtering, and Canny operator based on guided filtering), the proposed method exhibits a better SNR, a better ability to identify small faults, and robustness to noise. This novel algorithm can control the balance between noise attenuation and effective signal preservation as well as effectively detect faults in seismic data. Therefore, the proposed method effectively improves the fault identification accuracy, facilitates the gas-bearing analysis of the structure, provides guidance for the actual well location deployment of the project, and has important practical significance for oil and gas exploration and development.

About this title - Seismic Characterization of Carbonate Platforms and Reservoirs

10.1144/sp509 ◽  
2021 ◽  
Vol 509 (1) ◽  
pp. NP-NP
Author(s):  
J. Hendry ◽  
P. Burgess ◽  
D. Hunt ◽  
X. Janson ◽  
V. Zampetti
Keyword(s):  
Seismic Data ◽  
Oil And Gas ◽  
Carbonate Platform ◽  
Carbonate Platforms ◽  
Oil And Gas Exploration ◽  
Seismic Modelling ◽  
Flow Units ◽  
Development Data ◽  
Seismic Characterization

Modern seismic data have become an essential toolkit for studying carbonate platforms and reservoirs in impressive detail. Whilst driven primarily by oil and gas exploration and development, data sharing and collaboration are delivering fundamental geological knowledge on carbonate systems, revealing platform geomorphologies and how their evolution on millennial time scales, as well as kilometric length scales, was forced by long-term eustatic, oceanographic or tectonic factors. Quantitative interrogation of modern seismic attributes in carbonate reservoirs permits flow units and barriers arising from depositional and diagenetic processes to be imaged and extrapolated between wells.This volume reviews the variety of carbonate platform and reservoir characteristics that can be interpreted from modern seismic data, illustrating the benefits of creative interaction between geophysical and carbonate geological experts at all stages of a seismic campaign. Papers cover carbonate exploration, including the uniquely challenging South Atlantic pre-salt reservoirs, seismic modelling of carbonates, and seismic indicators of fluid flow and diagenesis.

Machine Learning Assisted Interpretation: Integrated Fault Prediction Extraction Case Study from the Groningen Gas Field, Netherlands

2021 ◽  
pp. 1-67
Author(s):  
Stewart Smith ◽  
Olesya Zimina ◽  
Surender Manral ◽  
Michael Nickel
Keyword(s):  
Machine Learning ◽  
Fault Detection ◽  
Seismic Data ◽  
Fault Prediction ◽  
Machine Learning Techniques ◽  
Gas Field ◽  
Seismic Fault ◽  
Learning Techniques ◽  
Groningen Gas Field

Seismic fault detection using machine learning techniques, in particular the convolution neural network (CNN), is becoming a widely accepted practice in the field of seismic interpretation. Machine learning algorithms are trained to mimic the capabilities of an experienced interpreter by recognizing patterns within seismic data and classifying them. Regardless of the method of seismic fault detection, interpretation or extraction of 3D fault representations from edge evidence or fault probability volumes is routine. Extracted fault representations are important to the understanding of the subsurface geology and are a critical input to upstream workflows including structural framework definition, static reservoir and petroleum system modeling, and well planning and de-risking activities. Efforts to automate the detection and extraction of geological features from seismic data have evolved in line with advances in computer algorithms, hardware, and machine learning techniques. We have developed an assisted fault interpretation workflow for seismic fault detection and extraction, demonstrated through a case study from the Groningen gas field of the Upper Permian, Dutch Rotliegend; a heavily faulted, subsalt gas field located onshore, NE Netherlands. Supervised using interpreter-led labeling, we apply a 2D multi-CNN to detect faults within a 3D pre-stack depth migrated seismic dataset. After prediction, we apply a geometric evaluation of predicted faults, using a principal component analysis (PCA) to produce geometric attribute representations (strike azimuth and planarity) of the fault prediction. Strike azimuth and planarity attributes are used to validate and automatically extract consistent 3D fault geometries, providing geological context to the interpreter and input to dependent workflows more efficiently.

High-resolution seismic processing technique with broadband,wide-azimuth, and high-density seismic data - A case study of thin-sand reservoir in eastern China

2021 ◽  
pp. 1-45
Author(s):  
Qin Su ◽  
Huahui Zeng ◽  
Yancan Tian ◽  
HaiLiang Li ◽  
Lei Lyu ◽  
...  
Keyword(s):  
Seismic Data ◽  
Oil And Gas ◽  
Single Point ◽  
Eastern China ◽  
High Density ◽  
Songliao Basin ◽  
Seismic Processing ◽  
Oil And Gas Exploration ◽  
Sand Body

Seismic processing and interpretation techniques provide important tools for the oil and gas exploration of the Songliao Basin in eastern China, which is dominated by terrestrial facies. In the Songliao Basin, a large number of thin-sand reservoirs are widely distributed, which are the primary targets of potential oil and gas exploration and exploitation. An important job of the exploration in the Songliao Basin is to accurately describe the distribution of these thin-sand belts and the sand-body shapes. However, the thickness of these thin-sand reservoirs are generally below the resolution of the conventional seismic processing. Most of the reservoirs are thin-interbeds of sand and mudstones with strong vertical and lateral variations. This makes it difficult to accurately predict the vertical and horizontal distribution of the thin-sand bodies using the conventional seismic processing and interpretation methods. Additionally, these lithologic traps are difficult to identify due to the complex controlling factor and distribution characteristics, and strong concealment. These challenges motivate us to improve the seismic data quality to help delineate the thin-sand reservoirs. In this paper, we use the broadband, wide-azimuth, and high-density integrated seismic exploration technique to help delineate the thin-reservoirs. We first use field single-point excitation and single-point receiver acquisition to obtain seismic data with wide frequency-bands, wide-azimuth angles, and high folds, which contain rich geological information. Next, we perform the near-surface Q-compensation, viscoelastic prestack time migration, seismic attributes, and seismic waveform indication inversion on the new acquired seismic data. The 3D case study indicates the benefits of improving the imaging of thin-sand body and the accuracy of inversion and reservoir characterization using the method in this paper.

Automatic, geologic layer-constrained well-seismic tie through blocked dynamic warping

2017 ◽  
Vol 5 (3) ◽  
pp. SJ81-SJ90 ◽  
Author(s):  
Kainan Wang ◽  
Jesse Lomask ◽  
Felix Segovia
Keyword(s):  
Seismic Data ◽  
Oil And Gas ◽  
Synthetic Data ◽  
Optimal Solution ◽  
Velocity Model ◽  
Data Set ◽  
Oil And Gas Exploration ◽  
Interval Velocity ◽  
Velocity Changes ◽  
Dynamic Warping

Well-log-to-seismic tying is a key step in many interpretation workflows for oil and gas exploration. Synthetic seismic traces from the wells are often manually tied to seismic data; this process can be very time consuming and, in some cases, inaccurate. Automatic methods, such as dynamic time warping (DTW), can match synthetic traces to seismic data. Although these methods are extremely fast, they tend to create interval velocities that are not geologically realistic. We have described the modification of DTW to create a blocked dynamic warping (BDW) method. BDW generates an automatic, optimal well tie that honors geologically consistent velocity constraints. Consequently, it results in updated velocities that are more realistic than other methods. BDW constrains the updated velocity to be constant or linearly variable inside each geologic layer. With an optimal correlation between synthetic seismograms and surface seismic data, this algorithm returns an automatically updated time-depth curve and an updated interval velocity model that still retains the original geologic velocity boundaries. In other words, the algorithm finds the optimal solution for tying the synthetic to the seismic data while restricting the interval velocity changes to coincide with the initial input blocking. We have determined the application of the BDW technique on a synthetic data example and field data set.

PetroSPIRE: Indexing and retrieval of seismic data for oil and gas exploration

2003 ◽  
Author(s):  
Yuan‐Chi Chang ◽  
Matthew Hill ◽  
Chung‐Sheng Li ◽  
Randy Pepper
Keyword(s):  
Seismic Data ◽  
Oil And Gas ◽  
Oil And Gas Exploration ◽  
Indexing And Retrieval

Hydrocarbon identification using the AVO response correction method based on high-resolution complex spectral decomposition

2020 ◽  
Vol 8 (1) ◽  
pp. SA49-SA61
Author(s):  
Huihuang Tan ◽  
Donghong Zhou ◽  
Shengqiang Zhang ◽  
Zhijun Zhang ◽  
Xinyi Duan ◽  
...  
Keyword(s):  
High Resolution ◽  
Seismic Data ◽  
Spectral Decomposition ◽  
Oil And Gas ◽  
Low Frequency ◽  
Seismic Signal ◽  
Correction Method ◽  
Bohai Bay ◽  
Oil And Gas Exploration ◽  
Response Correction

Amplitude-variation-with-offset (AVO) technique is one of the primary quantitative hydrocarbon discrimination methods with prestack seismic data. However, the prestack seismic data are usually have low data quality, such as nonflat gathers and nonpreserved amplitude due to absorption, attenuation, and/or many other reasons, which usually lead to a wrong AVO response. The Neogene formations in the Huanghekou area of the Bohai Bay Basin are unconsolidated clastics with a high average porosity, and we find that the attenuation on seismic signal is very strong, which causes an inconsistency of AVO responses between seismic gathers and its corresponding synthetics. Our research results indicate that the synthetic AVO response can match the field seismic gathers in the low-frequency end, but not in the high-frequency components. Thus, we have developed an AVO response correction method based on high-resolution complex spectral decomposition and low-frequency constraint. This method can help to achieve a correct high-resolution AVO response. Its application in Bohai oil fields reveals that it is an efficient way to identify hydrocarbons in rocks, which provides an important technique for support in oil and gas exploration and production in this area.

Classification of Tight Sandstone Reservoir Based on the Conventional Logging

2014 ◽  
Vol 633-634 ◽  
pp. 526-529 ◽  
Author(s):  
Xiao Ling Xiao ◽  
Jia Li Cui ◽  
Yu Peng Zhang ◽  
Xiang Zhang ◽  
Han Wu
Keyword(s):  
Support Vector Machine ◽  
Oil And Gas ◽  
Identification Accuracy ◽  
Support Vector ◽  
Tight Sandstone ◽  
Oil And Gas Exploration ◽  
Unconventional Oil ◽  
Unconventional Oil And Gas ◽  
Sandstone Reservoir

With the increasing social demand for oil and gas resources, the exploration and development of unconventional oil and gas reservoirs will pay more and more attention. Tight sandstone reservoir classification is one of the important tasks in the research of unconventional oil and gas exploration and development.Limitations exist in tight sandstone reservoir classification by various conventional logging.A method for the classification of tight sandstone reservoir based on support vector machine is presented in this paper, combining with the core data and flow unit to establish the reservoir classification standard. Tight sandstone reservoirs of no coring wells are classified based on the model made by support vector machine using conventional logging.The application results show that this method has high suitability and identification accuracy.

scholarly journals SUBSURFACE STRESS PREDICTION USING SEISMIC DATA FOR OIL AND GAS EXPLORATION

2016 ◽  
Vol 34 (1) ◽  
Author(s):  
Lourenildo W.B. Leite ◽  
Wildney W.S. Vieira ◽  
Boris Sibiryakov
Keyword(s):  
Seismic Data ◽  
Oil And Gas ◽  
Research Study ◽  
Sedimentary Basin ◽  
Sedimentary Basins ◽  
Basin Modeling ◽  
Oil And Gas Exploration ◽  
Stress Prediction ◽  
Subsurface Stress ◽  
Scientific Theme

ABSTRACT. The present paper is part of a major research study that has for objective the prediction of stress in sedimentary basins, as a contribution to geological and engineering methods and techniques for oil and gas exploration. Such an attractive and important scientific theme is based on the knowledge of the compressional...Keywords: sedimentary basin modeling, pressure prediction, subsurface stress. RESUMO. O presente trabalho faz parte de um projeto de estudomaior que tem por objetivo a predição de tensões embacias sedimentares, como uma contribuição aos métodos e técnicas da geologia e da engenharia de exploração de óleo e gás. Este assunto científico, atrativo e importante, é baseado...Palavras-chave: modelagem de bacia sedimentar, predição de pressão, tensão na subsuperfície.

Redefined Distribution of the Permian Volcanic Rocks in the Tarim Basin: Based on Logging and Seismic Data

2013 ◽  
Vol 448-453 ◽  
pp. 3723-3727 ◽  
Author(s):  
Yun Pan ◽  
Zong Xiu Wang ◽  
Mao Pan
Keyword(s):  
Tarim Basin ◽  
Seismic Data ◽  
Oil And Gas ◽  
Volcanic Rocks ◽  
Oil Field ◽  
Shielding Effect ◽  
Underlying Structure ◽  
Oil Exploration ◽  
Oil And Gas Exploration ◽  
The North

There are a lot of Permian volcanic rocks which are widely distributed in Tarim Basin. Because of the shielding effect of the volcanic rocks to the underlying structure, the distribution of the volcanic rocks in Tarim Basin is very important to the deep oil and gas exploration. However, with the progress of oil exploration in Tarim oil field in recent years, much more logging and seismic data is available. Based on the model of logging-seismic integrated identification, the distribution of the Permian volcanic rocks is revised by using the drilling, logging and seismic data. It shows that the rhyolite is mainly distributed in the north basin, and the basalt is widely distributed in the basin. Moreover, the basalt has larger area than which delineated by other people.

Oil and gas exploration in Australia in 2014—a year of extremes

2015 ◽  
Vol 55 (1) ◽  
pp. 163 ◽  
Author(s):  
Peter Stickland
Keyword(s):  
Seismic Data ◽  
Oil And Gas ◽  
Business Environment ◽  
Oil Price ◽  
Gas Flows ◽  
Leading Indicators ◽  
Unconventional Gas ◽  
Oil And Gas Exploration ◽  
Seismic Data Acquisition ◽  
Cooper Basin

In 2014, explorers in Australia experienced a range of highs and lows. There have been discoveries in new play types such as Phoenix South–1 in the Roebuck Basin, offshore WA, as well as discoveries that rejuvenate mature basins such as Seneco–3 in the onshore Perth Basin and a number of wells demonstrating unconventional gas flows in the Cooper Basin. Exploration lows include the inevitable unsuccessful wells, the general low level of drilling activity both offshore and in some states, frustrations at approval delays and constraints—particularly in NSW and Victoria—and the sharply contracting business environment towards the end of 2014 as the oil price rapidly fell to its lowest levels in five years. This PESA review looks in detail at the trends and highlights for oil and gas exploration both onshore and offshore Australia in 2014; not just outcomes with the drill bit, but also leading indicators such as seismic data acquisition and permit awards. It also seeks to be insightful and to make conclusions about the condition of oil and gas exploration in Australia, as well as comment on future implications for the industry.

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