Layers and bright spots

Geophysics ◽  
1986 ◽  
Vol 51 (3) ◽  
pp. 699-709 ◽  
Author(s):  
H. Almoghrabi ◽  
J. Lange
Keyword(s):  
A Priori ◽  
Plane Layer ◽  
Pore Fluid ◽  
Bright Spot ◽  
Amplitude Analysis ◽  
Converted Wave ◽  
Incident Wavelength ◽  
Field Development ◽  
Bright Spots ◽  
Spot Data

Seismic amplitudes are affected by both geometric and lithologic features of reflecting layers. Observation of “bright spots” is a function of not only pore fluid saturations, but also of layer thickness and surrounding rock type. The numerical model developed uses a finite sum of reflected and mode‐converted waves to evaluate the application of wave analysis in determining pore fluid types. Amplitude analysis alone is not sufficient to define realistically pore fluid type, but when amplitude analysis is combined with phase and mode‐converted shear‐wave behavior, it is possible to differentiate between pore fluid types. Various configurations which lead to bright spots, including coal and limestone layers, are evaluated. An algorithm is developed, based on the numerical examples, which can differentiate gas zones from other bright spot data. Thickness of the plane layer is an important factor in defining the overall reflectivity due to interference of the reflected wave components. Gas saturation of a layer is not a sufficient condition for a bright spot, but can lead to “dull spots” for layers in the right thickness range (relative to the incident wavelength). The lithology of the boundary material determines the extremes in amplitude variation which result when thickness or wavelength is varied. If a priori knowledge of the lithology or thickness of the structure is available, the amplitude‐phase‐converted wave algorithm can be applied to other than bright spot data to characterize the structure. This indicates there are important applications of the amplitude‐phase‐converted wave algorithm to field development and to bright spot analysis for exploration.

Analysis of conventional and converted mode reflections at Putah sink, California using three‐component data

Geophysics ◽  
1990 ◽  
Vol 55 (6) ◽  
pp. 646-659 ◽  
Author(s):  
C. Frasier ◽  
D. Winterstein
Keyword(s):  
Time Window ◽  
Structural Features ◽  
Low Noise ◽  
P Wave ◽  
Bright Spot ◽  
High Signal ◽  
Converted Wave ◽  
Gas Field ◽  
Seismic Line ◽  
S Waves

In 1980 Chevron recorded a three‐component seismic line using vertical (V) and transverse (T) motion vibrators over the Putah sink gas field near Davis, California. The purpose was to record the total vector motion of the various reflection types excited by the two sources, with emphasis on converted P‐S reflections. Analysis of the conventional reflection data agreed with results from the Conoco Shear Wave Group Shoot of 1977–1978. For example, the P‐P wave section had gas‐sand bright spots which were absent in the S‐S wave section. Shot profiles from the V vibrators showed strong P‐S converted wave events on the horizontal radial component (R) as expected. To our surprise, shot records from the T vibrators showed S‐P converted wave events on the V component, with low amplitudes but high signal‐to‐noise (S/N) ratios. These S‐P events were likely products of split S‐waves generated in anisotropic subsurface media. Components of these downgoing waves in the plane of incidence were converted to P‐waves on reflection and arrived at receivers in a low‐noise time window ahead of the S‐S waves. The two types of converted waves (P‐S and S‐P) were first stacked by common midpoint (CMP). The unexpected S‐P section was lower in true amplitude but much higher in S/N ratio than the P‐S section. The Winters gas‐sand bright spot was missing on the converted wave sections, mimicking the S‐S reflectivity as expected. CRP gathers were formed by rebinning data by a simple ray‐tracing formula based on the asymmetry of raypaths. CRP stacking improved P‐S and S‐P event resolution relative to CMP stacking and laterally aligned structural features with their counterparts on P and S sections. Thus, the unexpected S‐P data provided us with an extra check for our converted wave data processing.

GOLDEN BEACH: A BRIGHT SPOT

1978 ◽  
Vol 18 (1) ◽  
pp. 109
Author(s):  
R. B. Mariow
Keyword(s):  
Seismic Data ◽  
High Amplitude ◽  
Late Eocene ◽  
Polarity Reversal ◽  
Bright Spot ◽  
Areal Extent ◽  
Water Contact ◽  
Bright Spots ◽  
Gippsland Basin ◽  
Seismic Reflector

The Golden Beach closed anticlinal structure lies five kilometres offshore in the Gippsland Basin. Golden Beach 1A was drilled in 1967 near the crest of the structure and intersected a gas column of 19 m (63 feet) at the top of the Latrobe Group (Late Eocene) where most of the hydrocarbon accumulations in the Gippsland Basin have been found. The gas-water contact lies at a depth of 652 m (2139 feet) below sea level.On seismic data recorded over the structure, a high amplitude flat-lying event was interpreted as a bright 'flat spot' at the gas-water contact. Reprocessing of the seismic data enhanced the bright spot effect and enabled the areal extent of the gas zone to be mapped. The presence of the gas also leads to a polarity reversal of the top of the Latrobe Group seismic reflector over the gas accumulation.Seismic data from other structures containing hydrocarbons in the Gippsland Basin support the concept that bright spots and flat spots are more likely to be associated with gas than with oil accumulations, and that the observed bright spot effect decreases with increasing depth.

A SIMPLE UPGRADE FOR SOME BRIGHT SPOTS

Geophysics ◽  
1977 ◽  
Vol 42 (4) ◽  
pp. 868-871 ◽  
Author(s):  
Jerry A. Ware
Keyword(s):  
Constant Velocity ◽  
Bright Spot ◽  
Ray Theory ◽  
Multiple Reflections ◽  
Low Velocity ◽  
Reasonable Estimate ◽  
Raw Data ◽  
Common Depth Point ◽  
Bright Spots ◽  
The Common

Confirmation that a bright spot zone in question is low velocity can sometimes be made by looking at constant velocity stacks or the common‐depth‐point gathers. When this confirmation does exist, then it is usually possible to do simple ray theory to get a reasonable estimate of the pay thickness, especially if the water‐sand velocity and the gas‐sand velocity are either known or can be predicted for the area. The confirmation referred to can take the form of under‐removal of the primary events or be exhibited by multiple reflections from the bright spot zone. Such under‐removals or multiple reflections will not be seen on the stacked sections but are sometimes obvious on the raw data, such as the common‐depth‐point gathers, or can be implied by looking at constant velocity stacks of the zone in question at different stacking velocities.

Prestack amplitude analysis methodology and application to seismic bright spots in the Po Valley, Italy

Geophysics ◽  
1990 ◽  
Vol 55 (2) ◽  
pp. 157-166 ◽  
Author(s):  
Alfredo Mazzotti
Keyword(s):  
Amplitude Analysis ◽  
Borehole Data ◽  
Seismic Section ◽  
Po Valley ◽  
Gravel Layer ◽  
Amplitude Versus Offset ◽  
Bright Spots ◽  
Head Waves ◽  
Amplitude Anomaly ◽  
Zero Offset

The amplitude‐versus‐offset (AVO) characteristics of three separate bright spots on the same seismic section are analyzed. One of the bright spots results from a water‐bearing gravel layer, and the others correspond to gas‐saturated sandy beds. The amplitude analysis includes reflections from the entire range of incidence angles available from the survey; for the shallower amplitude anomaly, these angles reached values up to 66°. Extension of the analysis to longer offsets is aimed at detecting possible critical‐angle phenomena in order to reduce the uncertainty when the zero‐offset reflection’s polarity is unknown. The reflection from the gravel layer has this property. Its amplitude exhibits an initial decrease followed by a sudden rise in the AVO trend due to critical reflection and head waves. The gas‐related anomalies have a much different AVO characteristic, one in which the amplitude increases with offset distance. Two seismic events located above the bright spots were also investigated to further verify the validity of the seismic amplitude processing. The AVO trends of the three bright spots and of the two reference levels were compared with analogous trends of synthetic seismograms that were computed from models derived from borehole data.

Geological origins of seismic bright spot reflections in the Ordovician strata in the Halahatang area of the Tarim Basin, western China

2018 ◽  
Vol 55 (12) ◽  
pp. 1297-1311 ◽  
Author(s):  
Wei Yang ◽  
Xiaoxing Gong ◽  
Wenjie Li
Keyword(s):  
Tarim Basin ◽  
Oil And Gas ◽  
High Amplitude ◽  
Hydrothermal Activity ◽  
Hydrocarbon Exploration ◽  
Western China ◽  
Bright Spot ◽  
Gas Reservoirs ◽  
Seismic Section ◽  
Bright Spots

Anomalously high-amplitude seismic reflections are commonly observed in deeply buried Ordovician carbonate strata in the Halahatang area of the northern Tarim Basin. These bright spots have been demonstrated to be generally related to effective oil and gas reservoirs. These bright spot reflections have complex geological origins, because they are deeply buried and have been altered by multi-phase tectonic movement and karstification. Currently, there is no effective geological model for these bright spots to guide hydrocarbon exploration and development. Using core, well logs, and seismic data, the geological origins of bright spot are classified into three types, controlled by karstification, faulting, and volcanic hydrothermal activity. Bright spots differing by geological origin exhibit large differences in seismic reflection character, such as reflection amplitude, curvature, degree of distortion, and the number of vertically stacked bright spots in the seismic section. By categorizing the bright spots and the seismic character of the surrounding strata, their geological origins can after be inferred. Reservoirs formed by early karstification were later altered by epigenetic karstification. Two periods of paleodrainage further altered the early dissolution pores. In addition, faults formed by tectonic uplift also enhanced the dissolution of the flowing karst waters. Some reservoirs were subsequently altered by Permian volcanic hydrothermal fluids.

Bright spots, dim spots: Geologic controls of direct hydrocarbon indicator type, magnitude, and detectability, Niger Delta Basin

2016 ◽  
Vol 4 (3) ◽  
pp. SN45-SN69 ◽  
Author(s):  
Krzysztof M. Wojcik ◽  
Irene S. Espejo ◽  
Adebukonla M. Kalejaiye ◽  
Otuka K. Umahi
Keyword(s):  
Niger Delta ◽  
Soft Clay ◽  
Bright Spot ◽  
Systematic Analysis ◽  
Bright Spots ◽  
Key Factor ◽  
Well Data ◽  
Diagenetic Evolution ◽  
Niger Delta Basin ◽  
Fluid Signal

Bright-spot amplitude anomalies have been an attractive exploration target in the Niger Delta since the early 1970s, and the bright-spot play can now be considered mature. There is a need to extend the bright-spot exploration success to include other types of direct hydrocarbon indicators such as dim spots or polarity reversals. Several true dim spots have been identified in the basin, calibrated with well data and characterized in detail to enable a systematic analysis of the geologic factors that produce the dim-spot response. Dim spots in deeper stratigraphic intervals reflect a high degree of compaction and quartz cementation and are characterized by minimal fluid signal and commonly very low detectability. Robust and detectable dim spots have been identified in shallow marine/deltaic systems in the Niger Delta in shallower stratigraphic intervals with a relatively strong fluid signal. The key factor promoting a robust dim-spot response is the presence of acoustically soft, clay-rich shales as the bounding lithology. The variability of the bounding shales in the Niger Delta is stratigraphically constrained and, to some degree, predictable. The change from hard mudstones to soft claystones, which can be recognized in seismic data, may result in a transition from bright to dim spots, possibly taking place within the same stratigraphic interval and over short distances. Many clastic basins globally follow a similar stratigraphic and diagenetic evolution; thus, the Niger Delta example may be a good analog for dim-spot plays elsewhere.

Normal dimensions of the posterior pituitary bright spot on magnetic resonance imaging

2014 ◽  
Vol 120 (2) ◽  
pp. 357-362 ◽  
Author(s):  
Martin Côté ◽  
Karen L. Salzman ◽  
Mohammad Sorour ◽  
William T. Couldwell
Keyword(s):  
Bright Spot ◽  
Short Axis ◽  
Posterior Pituitary ◽  
Resonance Imaging ◽  
Normal Range ◽  
Pathological Conditions ◽  
Bright Spots ◽  
Individual Variations ◽  
The Mean ◽  
Pituitary Bright Spot

Object The normal pituitary bright spot seen on unenhanced T1-weighted MRI is thought to result from the T1-shortening effect of the vasopressin stored in the posterior pituitary. Individual variations in its size may be difficult to differentiate from pathological conditions resulting in either absence of the pituitary bright spot or in T1-hyperintense lesions of the sella. The objective of this paper was to define a range of normal dimensions of the pituitary bright spot and to illustrate some of the most commonly encountered pathologies that result in absence or enlargement of the pituitary bright spot. Methods The authors selected normal pituitary MRI studies from 106 patients with no pituitary abnormality. The size of each pituitary bright spot was measured in the longest axis and in the dimension perpendicular to this axis to describe the typical dimensions. The authors also present cases of patients with pituitary abnormalities to highlight the differences and potential overlap between normal and pathological pituitary imaging. Results All of the studies evaluated were found to have pituitary bright spots, and the mean dimensions were 4.8 mm in the long axis and 2.4 mm in the short axis. The dimension of the pituitary bright spot in the long axis decreased with patient age. The distribution of dimensions of the pituitary bright spot was normal, indicating that 99.7% of patients should have a pituitary bright spot measuring between 1.2 and 8.5 mm in its long axis and between 0.4 and 4.4 mm in its short axis, an interval corresponding to 3 standard deviations below and above the mean. In cases where the dimension of the pituitary bright spot is outside this range, pathological conditions should be considered. Conclusions The pituitary bright spot should always be demonstrated on T1-weighted MRI, and its dimensions should be within the identified normal range in most patients. Outside of this range, pathological conditions affecting the pituitary bright spot should be considered.

scholarly journals Factors Associated With Successful Research Departments

2019 ◽  
Vol 51 (2) ◽  
Author(s):  
Winston Liaw ◽  
Aimee Eden ◽  
Megan Coffman ◽  
Meera Nagaraj ◽  
Andrew Bazemore
Keyword(s):  
Family Medicine ◽  
Interdisciplinary Teams ◽  
Bright Spot ◽  
Snowball Sampling ◽  
Medicine Research ◽  
School Based ◽  
Bright Spots ◽  
Semistructured Interviews ◽  
The Individual ◽  
Faculty Selection

Background and Objectives: Inadequate resources have led to family medicine research divisions at varying stages of development. The purpose of this analysis was to identify the factors that family medicine research “bright spot” departments perceive to be crucial to their success. Methods: In this qualitative analysis, we identified bright spot dimensions and used a snowball sampling approach to identify medical school-based departments considered to be research bright spots. With 16 leaders from eight departments, we conducted semistructured interviews, covering historical events, leadership, partnerships, mentors, faculty selection, and training. We recorded and transcribed interviews and used a template-driven approach to data analysis, iteratively defining and modifying codes. At least two reviewers independently coded each interview, and coding discrepancies were discussed until consensus was reached. Results: We identified the following themes: (1) Leadership was committed to research; (2) Research was built around teams of researchers; (3) Interdisciplinary teams facilitated by partnerships allowed the department to tackle complex problems; (4) The convergence of researchers and clinicians ensured that the research was relevant to family medicine; (5) Departments had cultures that engendered trust, leading to effective collaboration; (6) These teams were composed of intrinsically motivated individuals supported by mentorship and resources; (7) When deciding which questions to pursue, departments balanced the question’s alignment with the individual researcher’s passion, relevance to family medicine, and fundability. Conclusions: A commitment to research from an engaged chair, partnerships, integrating front-line clinicians, and supporting intrinsically motivated individuals were important for bright spots. Applying these concepts may be an important strategy for generating knowledge.

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