Elastic reflectivity vectors and the geometry of intercept-gradient crossplots

2019 ◽  
Vol 38 (10) ◽  
pp. 762-769
Author(s):  
Patrick Connolly
Keyword(s):  
Elastic Property ◽  
Elastic Properties ◽  
Wave Velocity ◽  
Seismic Data ◽  
Measurement Errors ◽  
Rock Physics ◽  
P Wave ◽  
S Wave ◽  
P Wave Velocity ◽  
Well Log Analysis

Reflectivities of elastic properties can be expressed as a sum of the reflectivities of P-wave velocity, S-wave velocity, and density, as can the amplitude-variation-with-offset (AVO) parameters, intercept, gradient, and curvature. This common format allows elastic property reflectivities to be expressed as a sum of AVO parameters. Most AVO studies are conducted using a two-term approximation, so it is helpful to reduce the three-term expressions for elastic reflectivities to two by assuming a relationship between P-wave velocity and density. Reduced to two AVO components, elastic property reflectivities can be represented as vectors on intercept-gradient crossplots. Normalizing the lengths of the vectors allows them to serve as basis vectors such that the position of any point in intercept-gradient space can be inferred directly from changes in elastic properties. This provides a direct link between properties commonly used in rock physics and attributes that can be measured from seismic data. The theory is best exploited by constructing new seismic data sets from combinations of intercept and gradient data at various projection angles. Elastic property reflectivity theory can be transferred to the impedance domain to aid in the analysis of well data to help inform the choice of projection angles. Because of the effects of gradient measurement errors, seismic projection angles are unlikely to be the same as theoretical angles or angles derived from well-log analysis, so seismic data will need to be scanned through a range of angles to find the optimum.

Using Seismic Data to Predict Shale Pore Pressure and Overpressure Sweet Spots: A Case Study from the Lower Silurian Longmaxi Formation in Sichuan Basin, China

2021 ◽  
Author(s):  
Sheng Chen ◽  
Qingcai Zeng ◽  
Xiujiao Wang ◽  
Qing Yang ◽  
Chunmeng Dai ◽  
...  
Keyword(s):  
Prediction Model ◽  
Wave Velocity ◽  
Shale Gas ◽  
Seismic Data ◽  
P Wave ◽  
Formation Pressure ◽  
S Wave ◽  
P Wave Velocity ◽  
New Formation ◽  
Sweet Spots

Abstract Practices of marine shale gas exploration and development in south China have proved that formation overpressure is the main controlling factor of shale gas enrichment and an indicator of good preservation condition. Accurate prediction of formation pressure before drilling is necessary for drilling safety and important for sweet spots predicting and horizontal wells deploying. However, the existing prediction methods of formation pore pressures all have defects, the prediction accuracy unsatisfactory for shale gas development. By means of rock mechanics analysis and related formulas, we derived a formula for calculating formation pore pressures. Through regional rock physical analysis, we determined and optimized the relevant parameters in the formula, and established a new formation pressure prediction model considering P-wave velocity, S-wave velocity and density. Based on regional exploration wells and 3D seismic data, we carried out pre-stack seismic inversion to obtain high-precision P-wave velocity, S-wave velocity and density data volumes. We utilized the new formation pressure prediction model to predict the pressure and the spatial distribution of overpressure sweet spots. Then, we applied the measured pressure data of three new wells to verify the predicted formation pressure by seismic data. The result shows that the new method has a higher accuracy. This method is qualified for safe drilling and prediction of overpressure sweet spots for shale gas development, so it is worthy of promotion.

scholarly journals Analisis Model Kecepatan Gelombang-P pada Coal-Seam Gas Studi Kasus Cekungan Sumatera Selatan, Indonesia

2020 ◽  
Vol 6 (2) ◽  
pp. 113-120
Author(s):  
Harnanti Yogaputri Hutami ◽  
Fitriyani Fitriyani ◽  
Tiara Larasati Priniarti ◽  
Handoyo Handoyo
Keyword(s):  
Coal Seam ◽  
Elastic Properties ◽  
Wave Velocity ◽  
Rock Physics ◽  
Velocity Model ◽  
Significant Negative Correlation ◽  
P Wave ◽  
Gas Content ◽  
Coal Seam Gas ◽  
P Wave Velocity

The rock physics model is one effective yet challenging way to investigate the coal-seam gas potential in Indonesia. However, because of the complex conditions of the Coal-Seam Gas Reservoirs, it is difficult to establish models. Despite the scarce modeling, this study aims to estimate the relation of gas-saturated within pores of coal seam to the elastic properties of rock, which is P-wave velocity. First, the coal seam minerals are applied to quantify matrix moduli using the Voigt-Reuss-Hill Average method. Pride’s simple equation is used to estimate the elastic properties of the coal seam at dry condition (zero gas saturation). Finally, Biot-Gassmann’s theory is applied to determine the elastic properties of coal seam with fully gas saturated. As the result, the proposed model showed that there is a significant negative correlation between gas content with both density and P-wave velocity of the coal seam. Finally, this P-wave velocity model of gas-saturated coal seams should be properly useful as the quick look for identifying coal seam gas potentials. 

Sediments with gas hydrates: Internal structure from seismic AVO

Geophysics ◽  
1998 ◽  
Vol 63 (5) ◽  
pp. 1659-1669 ◽  
Author(s):  
Christine Ecker ◽  
Jack Dvorkin ◽  
Amos Nur
Keyword(s):  
Internal Structure ◽  
Wave Velocity ◽  
Seismic Data ◽  
Pore Space ◽  
Rock Physics ◽  
P Wave ◽  
S Wave ◽  
High Concentration ◽  
Amplitude Variation With Offset ◽  
Bottom Simulating Reflector

We interpret amplitude variation with offset (AVO) data from a bottom simulating reflector (BSR) offshore Florida by using rock‐physics‐based synthetic seismic models. A previously conducted velocity and AVO analysis of the in‐situ seismic data showed that the BSR separates hydrate‐bearing sediments from sediments containing free methane. The amplitude at the BSR are increasingly negative with increasing offset. This behavior was explained by P-wave velocity above the BSR being larger than that below the BSR, and S-wave velocity above the BSR being smaller than that below the BSR. We use these AVO and velocity results to infer the internal structure of the hydrated sediment. To do so, we examine two micromechanical models that correspond to the two extreme cases of hydrate deposition in the pore space: (1) the hydrate cements grain contacts and strongly reinforces the sediment, and (2) the hydrate is located away from grain contacts and does not affect the stiffness of the sediment frame. Only the second model can qualitatively reproduce the observed AVO response. Thus inferred internal structure of the hydrate‐bearing sediment means that (1) the sediment above the BSR is uncemented and, thereby, mechanically weak, and (2) its permeability is very low because the hydrate clogs large pore‐space conduits. The latter explains why free gas is trapped underneath the BSR. The seismic data also indicate the absence of strong reflections at the top of the hydrate layer. This fact suggests that the high concentration of hydrates in the sediment just above the BSR gradually decreases with decreasing depth. This effect is consistent with the fact that the low‐permeability hydrated sediments above the BSR prevent free methane from migrating upwards.

Estimating shear‐wave velocities from P-wave and converted‐wave data

Geophysics ◽  
1999 ◽  
Vol 64 (2) ◽  
pp. 504-507 ◽  
Author(s):  
Franklyn K. Levin
Keyword(s):  
Wave Velocity ◽  
Seismic Data ◽  
P Wave ◽  
S Wave ◽  
Converted Wave ◽  
Wave Data ◽  
Wave Velocities ◽  
Shear Wave Velocities ◽  
P Wave Velocity ◽  
Growing Body

Tessmer and Behle (1988) show that S-wave velocity can be estimated from surface seismic data if both normal P-wave data and converted‐wave data (P-SV) are available. The relation of Tessmer and Behle is [Formula: see text] (1) where [Formula: see text] is the S-wave velocity, [Formula: see text] is the P-wave velocity, and [Formula: see text] is the converted‐wave velocity. The growing body of converted‐wave data suggest a brief examination of the validity of equation (1) for velocities that vary with depth.

scholarly journals Identification of hydrocarbons in chalk reservoirs from surface seismic data: South Arne field, North Sea

2005 ◽  
Vol 7 ◽  
pp. 13-16
Author(s):  
Peter Japsen ◽  
Anders Bruun ◽  
Ida L. Fabricius ◽  
Gary Mavko
Keyword(s):  
Wave Velocity ◽  
North Sea ◽  
Seismic Data ◽  
Pore Space ◽  
Sedimentary Rocks ◽  
Rock Physics ◽  
Acoustic Properties ◽  
P Wave ◽  
S Wave ◽  
Reservoir Rocks

Seismic data are mainly used to map out structures in the subsurface, but are also increasingly used to detect differences in porosity and in the fluids that occupy the pore space in sedimentary rocks. Hydrocarbons are generally lighter than brine, and the bulk density and sonic velocity (speed of pressure waves or P-wave velocity) of hydrocarbon-bearing sedimentary rocks are therefore reduced compared to non-reservoir rocks. However, sound is transmitted in different wave forms through the rock, and the shear velocity (speed of shear waves or S-wave velocity) is hardly affected by the density of the pore fluid. In order to detect the presence of hydrocarbons from seismic data, it is thus necessary to investigate how porosity and pore fluids affect the acoustic properties of a sedimentary rock. Much previous research has focused on describing such effects in sandstone (see Mavko et al. 1998), and only in recent years have corresponding studies on the rock physics of chalk appeared (e.g. Walls et al. 1998; Røgen 2002; Fabricius 2003; Gommesen 2003; Japsen et al. 2004). In the North Sea, chalk of the Danian Ekofisk Formation and the Maastrichtian Tor Formation are important reservoir rocks. More information could no doubt be extracted from seismic data if the fundamental physical properties of chalk were better understood. The presence of gas in chalk is known to cause a phase reversal in the seismic signal (Megson 1992), but the presence of oil in chalk has only recently been demonstrated to have an effect on surface seismic data (Japsen et al. 2004). The need for a better link between chalk reservoir parameters and geophysical observations has, however, strongly increased since the discovery of the Halfdan field proved major reserves outside four-way dip closures (Jacobsen et al. 1999; Vejbæk & Kristensen 2000).

Basin-wide empirical rock-physics transform and its application in Campeche Basin

2021 ◽  
Vol 40 (3) ◽  
pp. 178-185
Author(s):  
Yangjun (Kevin) Liu ◽  
Jonathan Hernandez Casado ◽  
Mohamed El-Toukhy ◽  
Shenghong Tai
Keyword(s):  
Pore Pressure ◽  
Wave Velocity ◽  
Effective Stress ◽  
Seismic Data ◽  
Sedimentary Basin ◽  
Rock Physics ◽  
P Wave ◽  
Rock Properties ◽  
Borehole Data ◽  
P Wave Velocity

Rock properties in the subsurface are of major importance for evaluating the petroleum prospectivity of a sedimentary basin. The key rock properties to understand are porosity, density, temperature, effective stress, and pore pressure. These rock properties can be obtained or calculated when borehole data are available. However, borehole data are usually sparse, especially in frontier basins. We propose some simple rock-physics transforms for converting P-wave velocity to other rock properties. We found that these rock-physics transforms are predictive in the east and west sides of Campeche Basin. The proposed rock-physics transforms can be used to obtain laterally varying rock properties based on information derived from seismic data.

3D-printed rock models: Elastic properties and the effects of penny-shaped inclusions with fluid substitution

Geophysics ◽  
2016 ◽  
Vol 81 (6) ◽  
pp. D669-D677 ◽  
Author(s):  
Long Huang ◽  
Robert R. Stewart ◽  
Nikolay Dyaur ◽  
Jose Baez-Franceschi
Keyword(s):  
3D Printing ◽  
Elastic Properties ◽  
Wave Velocity ◽  
Bedding Plane ◽  
P Wave ◽  
Fluid Substitution ◽  
S Wave ◽  
Wave Velocities ◽  
P Wave Velocity ◽  
3D Printed

3D printing techniques (additive manufacturing) using different materials and structures provide opportunities to understand porous or fractured materials and fluid effects on their elastic properties. We used a 3D printer (Stratasys Dimension SST 768) to print one “solid” cube model and another with penny-shaped inclusions. The 3D printing process builds materials, layer by layer, producing a slight “bedding” plane, somewhat similar to a sedimentary process. We used ultrasonic transducers (500 kHz) to measure the P- and S-wave velocities. The input printing material was thermoplastic with a density of [Formula: see text], P-wave velocity of [Formula: see text], and S-wave velocity of [Formula: see text]. The solid cube had a porosity of approximately 6% and a density of [Formula: see text]. Its P-wave velocity was [Formula: see text] in the bedding direction and [Formula: see text] normal to bedding. We observed S-wave splitting with fast and slow velocities of 879 and [Formula: see text], respectively. Quality factors for P- and S-waves were estimated using the spectral-ratio method with [Formula: see text] ranging from 15 to 17 and [Formula: see text] from 24 to 27. By introducing penny-shaped inclusions along the bedding direction in a 3D printed cube, we created a more porous volume with density of [Formula: see text] and porosity of 24%. The inclusions significantly decreased the P-wave velocity to 1706 and [Formula: see text] parallel and normal to the bedding plane. The fast and slow S-wave velocities also decreased to 812 and [Formula: see text]. A fluid substitution experiment, performed with water, increased (20%–46%) P-wave velocities and decreased (9%–10%) S-wave velocities. Theoretical predictions using Schoenberg’s linear-slip theory and Hudson’s penny-shaped theory were calculated, and we found that both theories matched the measurements closely (within 5%). The 3D printed material has interesting and definable properties and is an exciting new material for understanding wave propagation, rock properties, and fluid effects.

Poststack, prestack, and joint inversion of P- and S-wave data for Morrow A sandstone characterization

2015 ◽  
Vol 3 (3) ◽  
pp. SZ59-SZ92 ◽  
Author(s):  
Paritosh Singh ◽  
Thomas L. Davis ◽  
Bryan DeVault
Keyword(s):  
Wave Velocity ◽  
Seismic Data ◽  
Joint Inversion ◽  
Wave Impedance ◽  
P Wave ◽  
S Wave ◽  
Wave Data ◽  
Wave Inversion ◽  
Density Maps ◽  
P Wave Velocity

Exploration for oil-bearing Morrow sandstones using conventional seismic data/methods has a startlingly low success rate of only 3%. The S-wave velocity contrast between the Morrow shale and A sandstone is strong compared with the P-wave velocity contrast, and, therefore, multicomponent seismic data could help to characterize these reservoirs. The SV and SH data used in this study are generated using S-wave data from horizontal source and horizontal receiver recording. Prestack P- and S-wave inversions, and joint P- and S-wave inversions, provide estimates of P- and S-wave impedances, and density for characterization of the Morrow A sandstone. Due to the weak P-wave amplitude-versus-angle response at the Morrow A sandstone top, the density and S-wave impedance estimated from joint P- and S-wave inversions were inferior to the prestack S-wave inversion. The inversion results were compared with the Morrow A sandstone thickness and density maps obtained from well logs to select the final impedance and density volume for interpretation. The P-wave impedance estimated from prestack P-wave data, as well as density and S-wave impedance estimated from prestack SV‐wave data were used to identify the distribution, thickness, quality, and porosity of the Morrow A sandstone. The stratal slicing method was used to get the P- and S-wave impedances and density maps. The S-wave impedance characterizes the Morrow A sandstone distribution better than the P-wave impedance throughout the study area. Density estimation from prestack inversion of SV data was able to distinguish between low- and high-quality reservoirs. The porosity volume was estimated from the density obtained from prestack SV-wave inversion. We found some possible well locations based on the interpretation.

Interpretation of AVO anomalies

Geophysics ◽  
2010 ◽  
Vol 75 (5) ◽  
pp. 75A3-75A13 ◽  
Author(s):  
Douglas J. Foster ◽  
Robert G. Keys ◽  
F. David Lane
Keyword(s):  
Wave Velocity ◽  
Seismic Data ◽  
P Wave ◽  
Rock Properties ◽  
Light Hydrocarbons ◽  
S Wave ◽  
Amplitude Variation With Offset ◽  
P Wave Velocity ◽  
Fluid Properties ◽  
Porosity Changes

We investigate the effects of changes in rock and fluid properties on amplitude-variation-with-offset (AVO) responses. In the slope-intercept domain, reflections from wet sands and shales fall on or near a trend that we call the fluid line. Reflections from the top of sands containing gas or light hydrocarbons fall on a trend approximately parallel to the fluid line; reflections from the base of gas sands fall on a parallel trend on the opposing side of the fluid line. The polarity standard of the seismic data dictates whether these reflections from the top of hydrocarbon-bearing sands are below or above the fluid line. Typically, rock properties of sands and shales differ, and therefore reflections from sand/shale interfaces are also displaced from the fluid line. The distance of these trends from the fluid line depends upon the contrast of the ratio of P-wave velocity [Formula: see text] and S-wave velocity [Formula: see text]. This ratio is a function of pore-fluid compressibility and implies that distance from the fluid line increases with increasing compressibility. Reflections from wet sands are closer to the fluid line than hydrocarbon-related reflections. Porosity changes affect acoustic impedance but do not significantly impact the [Formula: see text] contrast. As a result, porosity changes move the AVO response along trends approximately parallel to the fluid line. These observations are useful for interpreting AVO anomalies in terms of fluids, lithology, and porosity.

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