THE TUBRIDGI GAS FIELD REJUVENATED

2001 ◽  
Vol 41 (1) ◽  
pp. 429
Author(s):  
R.J.W. Bunt ◽  
W.D. Powell ◽  
T. Scholefield
Keyword(s):  
Depth Map ◽  
Geophysical Data ◽  
Depth Image ◽  
Low Permeability ◽  
Geological Model ◽  
Structural Configuration ◽  
Gas Field ◽  
Structural Character ◽  
Variable Nature ◽  
Geological Information

Difficulties in defining the structural character of the reservoir horizons at the Tubridgi Gas Field arise from gas charging of thin, often laterally discontinuous, silts and sands within the overburden. The gas charging of these shallow, low permeability units results in a seismic representation of the field as a time low. Historically, conversion from time to a reliable depth image has been problematic due to the variable nature of the gas charging, the relatively sparse, multi-vintage 2D seismic coverage and the corresponding difficulties in defining an accurate velocity field.After the unsuccessful drilling program in 1997 when three out of the five wells were plugged and abandoned, a revised interpretation methodology was developed, incorporating all available geophysical data, but placing a much greater emphasis on geological information from each of the wells in the area.The new depth map and geological model were tested by the drilling of Tubridgi–16 to –18 in August 1999. These three wells intersected the Birdrong Sandstone within one metre of prognosis, with two wells located structurally up-dip of the previous 17 wells drilled on the field. This accuracy resulted in a 97% increase in remaining reserves and a much higher level of confidence in the structural configuration of the Tubridgi field.A core of the Lower Gearle Sandstone in the Tubridgi 18 well highlighted the potential of this zone which has subsequently been evaluated in greater detail and potentially represents an additional productive horizon for the field.

scholarly journals A Residual Network and FPGA Based Real-Time Depth Map Enhancement System

Entropy ◽  
2021 ◽  
Vol 23 (5) ◽  
pp. 546
Author(s):  
Zhenni Li ◽  
Haoyi Sun ◽  
Yuliang Gao ◽  
Jiao Wang
Keyword(s):  
Real Time ◽  
Super Resolution ◽  
Depth Map ◽  
Acquisition System ◽  
Depth Image ◽  
Fpga Design ◽  
Depth Sensing ◽  
Residual Network ◽  
Real Time Processing ◽  
Depth Maps

Depth maps obtained through sensors are often unsatisfactory because of their low-resolution and noise interference. In this paper, we propose a real-time depth map enhancement system based on a residual network which uses dual channels to process depth maps and intensity maps respectively and cancels the preprocessing process, and the algorithm proposed can achieve real-time processing speed at more than 30 fps. Furthermore, the FPGA design and implementation for depth sensing is also introduced. In this FPGA design, intensity image and depth image are captured by the dual-camera synchronous acquisition system as the input of neural network. Experiments on various depth map restoration shows our algorithms has better performance than existing LRMC, DE-CNN and DDTF algorithms on standard datasets and has a better depth map super-resolution, and our FPGA completed the test of the system to ensure that the data throughput of the USB 3.0 interface of the acquisition system is stable at 226 Mbps, and support dual-camera to work at full speed, that is, 54 fps@ (1280 × 960 + 328 × 248 × 3).

The Current Situation and Prospects of Development of Low Permeability Oil Reservoir

2013 ◽  
Vol 734-737 ◽  
pp. 1286-1289 ◽  
Author(s):  
Lin Cong ◽  
Wen Long Li ◽  
Jing Chao Lei ◽  
Ru Bin Li
Keyword(s):  
Research Methods ◽  
Oil And Gas ◽  
Low Permeability ◽  
Oil Reservoir ◽  
Oil Exploration ◽  
Gas Field ◽  
Oil And Gas Field ◽  
Low Permeability Reservoirs ◽  
Technical Measures ◽  
Exploration And Development

Internationally the research of low permeability oil reservoir is a difficult point in the exploration and development of oil and gas field. This thesis, based on the research methods of low permeability reservoirs at home and abroad, summaries several major problems encountered in the process of low permeability oil exploration and development under the current technical conditions as well as the corresponding, but more effective technical measures that need to be constantly improved. And that exploration and development of low permeability of the reservoir will be the main battle field for some time in the future of oil exploration and development.

The Amethyst Field, Blocks 47/8a, 47/9a, 47/13a, 47/14a, 47,15a, UK North Sea

1991 ◽  
Vol 14 (1) ◽  
pp. 387-393 ◽  
Author(s):  
C. R. Garland
Keyword(s):  
North Sea ◽  
Reservoir Quality ◽  
Geological Model ◽  
Gas Field ◽  
Seismic Parameters ◽  
Recoverable Reserves ◽  
High Production ◽  
Sandstone Formation ◽  
Phased Development ◽  
Overlying Strata

AbstractThe Amethyst gas field was discovered in 1970 by well 47/13-1. Subsequently it was appraised and delineated by 17 wells. It consists of at least five accumulations with modest vertical relief, the reservoir being thin aeolian and fluviatile sandstones of the Lower Leman Sandstone Formation. Reservoir quality varies from poor to good, high production rates being attained from the aeolian sandstones. Seismic interpretation has involved, in addition to conventional methods, the mapping of several seismic parameters, and a geological model for the velocity distribution in overlying strata.Gas in place is currently estimated at 1100 BCF, with recoverable reserves of 844 BCF. The phased development plan envisages 20 development wells drilled from four platforms, and first gas from the 'A' platforms was delivered in October 1990. A unitization agreement is in force between the nine partners, with a technical redetermination of equity scheduled to commence in 1991.

scholarly journals No-Reference Depth Map Quality Evaluation Model Based on Depth Map Edge Confidence Measurement in Immersive Video Applications

2019 ◽  
Vol 11 (10) ◽  
pp. 204 ◽  
Author(s):  
Dogan ◽  
Haddad ◽  
Ekmekcioglu ◽  
Kondoz
Keyword(s):  
Quality Evaluation ◽  
Evaluation Model ◽  
Depth Map ◽  
Depth Image ◽  
Depth Maps ◽  
Model Based ◽  
Objective Quality ◽  
Quality Evaluation Model ◽  
Confidence Measurement

When it comes to evaluating perceptual quality of digital media for overall quality of experience assessment in immersive video applications, typically two main approaches stand out: Subjective and objective quality evaluation. On one hand, subjective quality evaluation offers the best representation of perceived video quality assessed by the real viewers. On the other hand, it consumes a significant amount of time and effort, due to the involvement of real users with lengthy and laborious assessment procedures. Thus, it is essential that an objective quality evaluation model is developed. The speed-up advantage offered by an objective quality evaluation model, which can predict the quality of rendered virtual views based on the depth maps used in the rendering process, allows for faster quality assessments for immersive video applications. This is particularly important given the lack of a suitable reference or ground truth for comparing the available depth maps, especially when live content services are offered in those applications. This paper presents a no-reference depth map quality evaluation model based on a proposed depth map edge confidence measurement technique to assist with accurately estimating the quality of rendered (virtual) views in immersive multi-view video content. The model is applied for depth image-based rendering in multi-view video format, providing comparable evaluation results to those existing in the literature, and often exceeding their performance.

The Research of Gas-Water Relations in Low-Permeability Tight Sand Gas Reservoir - Taking Zizhou Gas Field for Example

2013 ◽  
Vol 734-737 ◽  
pp. 480-483
Author(s):  
Jun Bao Ma ◽  
Yu Long Ma ◽  
Chao Sun ◽  
Jian Guo Wang
Keyword(s):  
Water Relations ◽  
Water Distribution ◽  
Low Permeability ◽  
Distribution Law ◽  
Deep Basin ◽  
Gas Reservoir ◽  
Gas Field ◽  
Structural Position ◽  
Single Well ◽  
Tight Sand Gas

The gas-water relations of low-permeability tight sand gas reservoir are complex and not necessarily linked to the structural relief, phenomenon that water is distributed in high structural position while gas in low structural position is common what makes it difficult to make a refined description of gas-water relations and distribution low. The article takes Zizhou gas field for example, establishes 4 gas-water relations modes of single well to analyze some profiles where there is abnormal phenomenon water up gas down, the fact is that water and gas are distributed in different sand bodies and Zizhou Gas Field is not a deep basin gas reservoir. The research shows the phenomenon that water up gas down does not exist, the gas-water relations are normal. The research results have certain significance for the determination of gas-water distribution law.

scholarly journals Old well sidetracking selection standards: Sulige low-permeability gas field, China

2020 ◽  
Vol 10 (4) ◽  
pp. 1699-1709
Author(s):  
Yingzhong Yuan ◽  
Zhilin Qi ◽  
Wende Yan ◽  
Ji Zhang ◽  
Cen Chen
Keyword(s):  
Low Permeability ◽  
Gas Field

scholarly journals Multi-Focus Image Fusion and Depth Map Estimation Based on Iterative Region Splitting Techniques

2019 ◽  
Vol 5 (9) ◽  
pp. 73 ◽  
Author(s):  
Wen-Nung Lie ◽  
Chia-Che Ho
Keyword(s):  
Depth Map ◽  
Depth Image ◽  
Splitting Algorithm ◽  
Image Stack ◽  
Spatial Propagation ◽  
Focus Image ◽  
Block Based ◽  
Winner Take All ◽  
Region Splitting ◽  
Imaging Plane

In this paper, a multi-focus image stack captured by varying positions of the imaging plane is processed to synthesize an all-in-focus (AIF) image and estimate its corresponding depth map. Compared with traditional methods (e.g., pixel- and block-based techniques), our focus-based measures are calculated based on irregularly shaped regions that have been refined or split in an iterative manner, to adapt to different image contents. An initial all-focus image is first computed, which is then segmented to get a region map. Spatial-focal property for each region is then analyzed to determine whether a region should be iteratively split into sub-regions. After iterative splitting, the final region map is used to perform regionally best focusing, based on the Winner-take-all (WTA) strategy, i.e., choosing the best focused pixels from image stack. The depth image can be easily converted from the resulting label image, where the label for each pixel represents the image index from which the pixel with the best focus is chosen. Regions whose focus profiles are not confident in getting a winner of the best focus will resort to spatial propagation from neighboring confident regions. Our experiments show that the adaptive region-splitting algorithm outperforms other state-of-the-art methods or commercial software in synthesis quality (in terms of a well-known Q metric), depth maps (in terms of subjective quality), and processing speed (with a gain of 17.81~40.43%).

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