Characterizing tight sand gas reservoirs using 3D3C seismic data in Sulige gas field

2012 ◽  
Author(s):  
Daxing Wang ◽  
Yuhua Zhao ◽  
Mengbo Zhang ◽  
Yonggang Wang ◽  
Xinwei He ◽  
...  
Keyword(s):  
Seismic Data ◽  
Gas Reservoirs ◽  
Gas Field ◽  
Tight Sand Gas

3-D seismic imaging and seismic attribute analysis of genetic sequences deposited in low‐accommodation conditions

Geophysics ◽  
1996 ◽  
Vol 61 (5) ◽  
pp. 1351-1362 ◽  
Author(s):  
B. A. Hardage ◽  
D. L. Carr ◽  
D. E. Lancaster ◽  
J. L. Simmons ◽  
D. S. Hamilton ◽  
...  
Keyword(s):  
Seismic Data ◽  
Sediment Accumulation ◽  
Gas Reservoirs ◽  
Seismic Attribute ◽  
Gas Field ◽  
Reservoir System ◽  
Depositional Processes ◽  
Genetic Sequences ◽  
Data Windows ◽  
Reservoir Facies

A multidisciplinary team, composed of stratigraphers, petrophysicists, reservoir engineers, and geophysicists, studied a portion of Boonsville gas field in the Fort Worth Basin of North‐Central Texas to determine how modern geophysical, geological, and engineering techniques could be combined to understand the mechanisms by which fluvio‐deltaic depositional processes create reservoir compartmentalization in a low‐ to moderate‐accommodation basin. An extensive database involving well logs, cores, production, and pressure data from 200‐plus wells, [Formula: see text] [Formula: see text] of 3-D seismic data, vertical seismic profiles (VSPs), and checkshots was assembled to support this investigation. The reservoir system we studied was the Bend Conglomerate, a productive series of gas reservoirs composed of Middle Pennsylvanian fluvio‐deltaic clastics 900 to 1300 ft (275 to 400 m) thick in our project area. We were particularly interested in this reservoir system because evidence suggested that many of the sequences in this stratigraphic interval were deposited in low‐accommodation conditions (that is, in an environment where there was limited vertical space available for sediment accumulation), and our objective was to investigate how fluvio‐deltaic reservoirs were compartmentalized by low‐accommodation depositional processes. Using an extensive well log database (200 plus wells) and a core‐calibrated calculation of rock facies derived from these logs, we divided the Bend Conglomerate interval into ten genetic sequences, with each sequence being approximately 100 ft (30 m) thick. We then used local VSP and checkshot control to transform log‐measured depths of each sequence boundary to seismic two‐way time coordinates and identified narrow seismic data windows encompassing each sequence across the [Formula: see text] [Formula: see text] 3-D seismic grid. A series of seismic attributes was calculated in these carefully defined data windows to determine which attributes were reliable indicators of the presence of productive reservoir facies and which attributes could, therefore, reveal distinct reservoir compartments and potentially show where infield wells should be drilled to reach previously uncontacted gas reservoirs. Our best success was the seismic attribute correlations we found in the Upper and Lower Caddo sequences, at the top of the Bend Conglomerate. These sequences were deposited in a low‐accommodation setting, relative to other Boonsville sequences, and we found that reflection amplitude and instantaneous frequency, respectively, were reliable indicators of the areal distribution of reservoir facies in these low‐accommodation sequences.

Hydrocarbon indicators on seismic data: Insights from poroviscoelastic modeling, amplitude, and frequency variation with offsets from the Drake Point gas field, Western Arctic Islands, Canada

2014 ◽  
Vol 2 (4) ◽  
pp. SP45-SP59
Author(s):  
Mathieu J. Duchesne ◽  
Bernard Giroux ◽  
Kezhen Hu
Keyword(s):  
Seismic Data ◽  
Low Frequency ◽  
Frequency Variation ◽  
Class Iii ◽  
Gas Reservoirs ◽  
Gas Field ◽  
Amplitude Variation With Offset ◽  
Seismic Amplitude ◽  
Impedance Modeling ◽  
Western Arctic

The evaluation of drilling prospects is frequently based on seismic amplitude anomalies. To decipher “true” seismic prospects from “false” ones, we used poroviscoelastic (PVE) models, as opposed to other formalisms such as acoustic, elastic, viscoelastic, and poroelastic models, that provided a solution that takes into account solid and fluid attenuation mechanisms separately to model the earth’s response to the propagation of a seismic wavefield. Here, a PVE impedance modeling scheme was tested using seismic and well-log data collected on a conventional gas reservoir in the Canadian Arctic. Comparisons between seismic-to-well ties achieved using acoustic and PVE media indicated that the latter provided more realistic synthetic seismograms. Although prestack analysis revealed that the present lithological context was of class I amplitude variation with offset (AVO), the seismic signature observed was of class III AVO. Consequently, the increase in amplitude with offset was interpreted to be induced not by a lithological change (i.e., shale to sand) combined with a gas-charged interval, but rather by an increase in porosity within the sandstone reservoir itself where the gas has accumulated. Frequency variation with offset analysis using spectral decomposition, image low-frequency shadows on the far offsets attributed to the gas accumulation that were correlative with the AVO anomaly. This highlighted the importance of far offsets in anomalous amplitude and frequency events attributed to the occurrence of gas reservoirs observed on stacked data and that these events can be missed if seismic hydrocarbon indicators were solely investigated on stacked data. Finally, the method of analysis emphasized the importance of combining indirect arguments coming from the observation of prestack and stacked seismic data in the time and frequency domains for reducing risk to an acceptable level before a prospect can be drilled.

scholarly journals Prediction of Shale Gas Reservoirs Using Fluid Mobility Attribute Driven by Post-Stack Seismic Data: A Case Study from Southern China

2020 ◽  
Vol 11 (1) ◽  
pp. 219
Author(s):  
Jing Zeng ◽  
Alexey Stovas ◽  
Handong Huang ◽  
Lixia Ren ◽  
Tianlei Tang
Keyword(s):  
Shale Gas ◽  
Seismic Data ◽  
Spectral Decomposition ◽  
Southern China ◽  
Gas Reservoirs ◽  
Seismic Attribute ◽  
Longmaxi Formation ◽  
Shale Gas Reservoirs ◽  
The Sichuan Basin ◽  
Shale Reservoirs

Paleozoic marine shale gas resources in Southern China present broad prospects for exploration and development. However, previous research has mostly focused on the shale in the Sichuan Basin. The research target of this study is expanded to the Lower Silurian Longmaxi shale outside the Sichuan Basin. A prediction scheme of shale gas reservoirs through the frequency-dependent seismic attribute technology is developed to reduce drilling risks of shale gas related to complex geological structure and low exploration level. Extracting frequency-dependent seismic attribute is inseparable from spectral decomposition technology, whereby the matching pursuit algorithm is commonly used. However, frequency interference in MP results in an erroneous time-frequency (TF) spectrum and affects the accuracy of seismic attribute. Firstly, a novel spectral decomposition technology is proposed to minimize the effect of frequency interference by integrating the MP and the ensemble empirical mode decomposition (EEMD). Synthetic and real data tests indicate that the proposed spectral decomposition technology provides a TF spectrum with higher accuracy and resolution than traditional MP. Then, a seismic fluid mobility attribute, extracted from the post-stack seismic data through the proposed spectral decomposition technology, is applied to characterize the shale reservoirs. The application result indicates that the seismic fluid mobility attribute can describe the spatial distribution of shale gas reservoirs well without well control. Based on the seismic fluid mobility attribute section, we have learned that the shale gas enrich areas are located near the bottom of the Longmaxi Formation. The inverted velocity data are also introduced to further verify the reliability of seismic fluid mobility. Finally, the thickness map of gas-bearing shale reservoirs in the Longmaxi Formation is obtained by combining the seismic fluid mobility attribute with the inverted velocity data, and two favorable exploration areas are suggested by analyzing the thickness, structure, and burial depth. The present work can not only be used to evaluate shale gas resources in the early stage of exploration, but also help to design the landing point and trajectory of directional drilling in the development stage.

A Study of Downhole Drillable Pulsing Cementing Device with Low Frequency Self-Excited Hydraulic Oscillation and its Field Application

2012 ◽  
Vol 450-451 ◽  
pp. 1536-1539
Author(s):  
Cui Ping Nie ◽  
Deng Sheng Ye
Keyword(s):  
Setting Time ◽  
Low Frequency ◽  
Field Application ◽  
Displacement Efficiency ◽  
Cement Slurry ◽  
Gas Reservoirs ◽  
Gas Field ◽  
Gas Well ◽  
Hydraulic Oscillation ◽  
Injection Technology

Abstract: Usually we pay more attention on how to improve gas well cementing quality in engineering design and field operations, and there are so many studies on cement agents but few researches on cement slurry injection technology. The field practice proved that conventional cementing technology can not ensure the cementing quality especially in gas well and some abnormal pressure wells. Most of the study is concentrated on cement agents and some cementing aspects such as wellbore condition, casing centralization etc. All the factors analysis on cementing quality has pointed out that a combination of good agents and suitable measurements can improve cementing quality effectively. The essential factor in cementing is to enhance the displacement efficiency, but normal hole condition and casing centralization are the fundamental for cementing only. Pulsing cementing is the technology that it can improve the displacement efficiency especially in reservoir well interval, also it can shorten the period from initial to ultimate setting time for cement slurry or improve thickening characteristics, and then to inhibit the potential gas or water channeling. Based on systematically research, aiming at improving in 7″ liner cementing, where there are multi gas reservoirs in long interval in SiChuan special gas field, well was completed with upper 7″ liner and down lower 5″ liner, poor cementing bonding before this time. So we stressed on the study of a downhole low frequency self-excited hydraulic oscillation pulsing cementing drillable device and its application, its successful field utilization proved that it is an innovative tool, and it can improve cementing quality obviously.

A Dynamic Workflow of Well Health Issue Prediction – Sulfur Deposition

2021 ◽  
Author(s):  
Bashirul Haq
Keyword(s):  
Material Balance ◽  
Gas Production ◽  
Health Issue ◽  
Sulfur Deposition ◽  
Gas Reservoirs ◽  
Gas Field ◽  
Actual Performance ◽  
Sulphur Deposition ◽  
Balance Analysis ◽  
Sour Gas

Abstract Sour gas reservoirs are vital sources for natural gas production. Sulphur deposition in the reservoir reduces a considerable amount of gas production due to permeability reduction. Consequently, well health monitoring and early prediction of Sulphur deposition are crucial for effective gas production from a sour gas reservoir. Dynamic gas material balance analysis is a useful technique in calculating gas initially in place utilizing the flowing wellhead or bottom hole pressures and rates during the well's lifetime. The approach did not apply to monitor a producing gas's health well and detect Sulphur deposition. This work aims to (i) modify dynamic gas material balance equation by adding the Sulphur deposition term, (ii) build a model to predict and validate the issue utilizing the modified equation. A unique form of the flowing material balance is developed by including Sulphur residue term. The curve fitting tool and modified flowing gas material balance are applied to predict well-expected behaviour. The variation between expected and actual performance indicates the health issue of a well. Initial, individual components of the model are tested. Then the model is validated with the known values. The workflow is applied to active gas field and correctly detected the health issue. The novel workflow can accurately predict Sulphur evidence. Besides,the workflow can notify the production engineers to take corrective measures about the subject. Keywords: Sulfur deposition, Dynamic gas material balance analysis, Workflow

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.

Sign in / Sign up

Export Citation Format

Share Document