scholarly journals Hydrothermal Dolomite Paleokarst Reservoir Development in Wolonghe Gasfield, Sichuan Basin, Revealed by Seismic Characterization

Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 579
Author(s):  
Bole Gao ◽  
Fei Tian ◽  
Renfang Pan ◽  
Wenhao Zheng ◽  
Rong Li ◽  
...  
Keyword(s):  
Wave Velocity ◽  
Sichuan Basin ◽  
Oil And Gas ◽  
Carbonate Reservoir ◽  
P Wave ◽  
Distribution Model ◽  
S Wave ◽  
Secondary Porosity ◽  
Petrophysical Parameters ◽  
Hydrothermal Dolomite

Hydrothermal dolomite paleokarst reservoir is a type of porous carbonate reservoir, which has a secondary porosity and can store a large amount of oil and gas underground. The reservoir is formed by magnesium-rich hydrothermal fluids during the karstification and later stages of the transformation. Due to the strong heterogeneity and thin thickness of hydrothermal dolomite paleokarst reservoirs, it is a real challenge to characterize the spatial distribution of the reservoirs. In this paper, we studied the hydrothermal dolomite paleokarst reservoir in the Wolonghe gasfield of the eastern Sichuan Basin. First, based on detailed observations of core samples, the characteristics and storage space types of the dolomite reservoir were described. Secondly, the petrophysical parameters of the paleokarst reservoirs were analyzed, and then the indicator factor for the dolomite reservoirs was established. Thirdly, using the time–depth conversion method, the geological characteristics near boreholes were connected with a three-dimensional (3D) seismic dataset. Several petrophysical parameters were predicted by prestack synchronous inversion technology, including the P-wave velocity, S-wave velocity, P-wave impedance, and the hydrothermal dolomite paleokarst reservoir indicator factor. Finally, the hydrothermal dolomite paleokarst reservoirs were quantitatively predicted, and their distribution model was built. The 3D geophysical characterization approach improves our understanding of hydrothermal dolomite paleokarst reservoirs, and can also be applied to other similar heterogeneous reservoirs.

scholarly journals Optimization of Rock Physics Models by Combining the Differential Effective Medium (DEM) and Adaptive Batzle-Wang Methods in “R” Field, East Java

2019 ◽  
Vol 17 (2) ◽  
Author(s):  
M. Wahdanadi Haidar ◽  
Reza Wardhana ◽  
M. Iskan ◽  
M. Syamsu Rosid
Keyword(s):  
Elastic Modulus ◽  
Wave Velocity ◽  
Carbonate Rocks ◽  
Effective Medium ◽  
Carbonate Reservoir ◽  
P Wave ◽  
S Wave ◽  
P Wave Velocity ◽  
Reservoir Conditions ◽  
Pore Types

The pore systems in carbonate reservoirs are more complex than the pore systems in clastic rocks. There are three types of pores in carbonate rocks: interparticle pores, stiff pores and cracks. The complexity of the pore types can lead to changes in the P-wave velocity by up to 40%, and carbonate reservoir characterization becomes difficult when the S-wave velocity is estimated using the dominant interparticle pore type only. In addition, the geometry of the pores affects the permeability of the reservoir. Therefore, when modelling the elastic modulus of the rock it is important to take into account the complexity of the pore types in carbonate rocks. The Differential Effective Medium (DEM) is a method for modelling the elastic modulus of the rock that takes into account the heterogeneity in the types of pores in carbonate rocks by adding pore-type inclusions little by little into the host material until the required proportion of the material is reached. In addition, the model is optimized by calculating the bulk modulus of the fluid filler porous rock under reservoir conditions using the Adaptive Batzle-Wang method. Once a fluid model has been constructed under reservoir conditions, the model is entered as input for the P-wave velocity model, which is then used to estimate the velocity of the S-wave and the proportion of primary and secondary pore types in the rock. Changes in the characteristics of the P-wave which are sensitive to the presence of fluid lead to improvements in the accuracy of the P-wave model, so the estimated S-wave velocity and the calculated ratio of primary and secondary pores in the reservoir are more reliable.

High‐resolution crosswell imaging of a west Texas carbonate reservoir: Part 5—Core analysis

Geophysics ◽  
1995 ◽  
Vol 60 (3) ◽  
pp. 712-726 ◽  
Author(s):  
Richard C. Nolen‐Hoeksema ◽  
Zhijing Wang ◽  
Jerry M. Harris ◽  
Robert T. Langan
Keyword(s):  
Wave Velocity ◽  
Field Experiments ◽  
Velocity Ratio ◽  
Carbonate Reservoir ◽  
P Wave ◽  
Core Analysis ◽  
S Wave ◽  
Traveltime Tomography ◽  
West Texas ◽  
P Wave Velocity

We conducted a core analysis program to provide supporting data to a series of crosswell field experiments being carried out in McElroy Field by Stanford University’s Seismic Tomography Project. The objective of these experiments is to demonstrate the use of crosswell seismic profiling for reservoir characterization and for monitoring [Formula: see text] flooding. For these west Texas carbonates, we estimate that [Formula: see text] saturation causes P‐wave velocity to change by −1.9% (pooled average, range = −6.3 to +0.1%), S‐wave velocity by +0.6% (range = 0 to 2.7%), and the P‐to‐S velocity ratio by −2.4% (range = −6.4 to −0.3%). When we compare these results to the precisions we can expect from traveltime tomography (about ±1% for P‐ and S‐wave velocity and about ±2% for the P‐to‐S velocity ratio), we conclude that time‐lapse traveltime tomography is sensitive enough to resolve changes in the P‐wave velocity, S‐wave velocity, and P‐to‐S velocity ratio that result from [Formula: see text] saturation. We concentrated here on the potential for [Formula: see text] saturation to affect seismic velocities. The potential for [Formula: see text] saturation to affect other seismic properties, not discussed here, may prove to be more significant (e.g., P‐wave and S‐wave impedance).

scholarly journals Development a Statistical Relationship between Compressional Wave Velocity and Petrophysical Properties from Logs Data for JERIBE Formation ASMARI Reservoir in FAUQI Oil Field

2021 ◽  
Vol 22 (3) ◽  
pp. 1-9
Author(s):  
Qahtan Abdul Aziz ◽  
Hassan Abdul Hussein
Keyword(s):  
Wave Velocity ◽  
Compressional Wave ◽  
Oil Field ◽  
P Wave ◽  
Statistical Relationship ◽  
Compressional Wave Velocity ◽  
S Wave ◽  
Petrophysical Parameters ◽  
Fluid Saturation ◽  
P Wave Velocity

The Compressional-wave (Vp) data are useful for reservoir exploration, drilling operations, stimulation, hydraulic fracturing employment, and development plans for a specific reservoir. Due to the different nature and behavior of the influencing parameters, more complex nonlinearity exists for Vp modeling purposes. In this study, a statistical relationship between compressional wave velocity and petrophysical parameters was developed from wireline log data for Jeribe formation in Fauqi oil field south Est Iraq, which is studied using single and multiple linear regressions. The model concentrated on predicting compressional wave velocity from petrophysical parameters and any pair of shear waves velocity, porosity, density, and fluid saturation in carbonate rocks. A strong linear correlation between P-wave velocity and S-wave velocity and between P-wave velocity and density rock was found. The resulting linear equations can be used to estimate P-wave velocity from the S-wave velocity in the case of both. The results of multiple regression analysis indicated that the density, porosity, water-saturated, and shear wave velocity (VS) are strongly related to Vp.

TitleApplication of M4C P-wave and S-wave Joint Inversion in Shallow Reservoir Identification

2021 ◽  
Author(s):  
Sian Zhu ◽  
Hongtao Chen ◽  
Yongjun Hu ◽  
Feng Yang ◽  
Yubin Feng
Keyword(s):  
Wave Velocity ◽  
Oil And Gas ◽  
Joint Inversion ◽  
Wave Impedance ◽  
P Wave ◽  
Seismic Survey ◽  
Bohai Bay ◽  
S Wave ◽  
Bohai Bay Basin ◽  
Gas Reservoirs

Abstract The genetic mechanism of shallow gas reservoirs is complex, which is usually characterized by shallow burial depth, multiple types, low reserves and wide distribution, so that the inversion based on P-wave data alone may be ambiguous. For shallow reservoir with large lateral variation, it is hard to accurately predict oil and water distribution by conventional P-wave prestack inversion. Marine four-component (M4C) P-wave and S-wave joint inversion can solve the problem effectively. M4C seismic survey collects P-wave and S-wave seismic data. An initial model can be established based on fine structural interpretation of P-wave and S-wave data and S-wave compression pattern matching. It lays a good foundation for subsequent P-wave and S-wave joint inversion. Based on the P-wave seismic record equation proposed by Fatti et al., a seismic record equation from poststack P-wave and S-wave joint inversion was derived according to the relationship among reflection coefficient, P-wave impedance, S-wave impedance and density, then important lithologic parameters (P-wave impedance, S-wave impedance and density) were calculated, and finally the ratio of P-wave velocity to S-wave velocity which is more sensitive to oil and gas was obtained. According to the ratio of P-wave velocity to S-wave velocity, the oil and gas distribution was predicted in shallow Bohai Bay Basin. Application has proven that the inversion can well reflect the fluid distribution, and the coincidence between the inversion results and the drilling data is up to 85%.M4C seismic survey was conducted for the first time to the shallow oil and gas reservoirs with rapid lateral variation in the Bohai Bay Basin, and collected raw P-wave and S-wave seismic data. Based on the data, the precision and reliability of P-wave and S-wave joint inversion was improved. The results provided strong technical support to the reserves and production increase in the Bohai Bay Basin.

Joint petrophysical full-waveform inversion of the shallow-seismic and multi-offset GPR data

2021 ◽  
Author(s):  
Tan Qin ◽  
Thomas Bohlen ◽  
Yudi Pan
Keyword(s):  
Dielectric Permittivity ◽  
Wave Velocity ◽  
Waveform Inversion ◽  
P Wave ◽  
Relative Dielectric Permittivity ◽  
Full Waveform Inversion ◽  
S Wave ◽  
Petrophysical Parameters ◽  
Full Waveform ◽  
Shallow Seismic

<p>Shallow-seismic surface wave and ground penetrating radar (GPR) are employed in a wide range of engineering and geosciences applications. Full-waveform inversion (FWI) of either seismic or multi-offset GPR data are able to provide high-resolution subsurface characterization and have received particular attention in the past decade. Those two geophysical methods are involved in the increasing requirements of comprehensive site and material investigations. However, it is still challenging to provide an effective integration between seismic data and electromagnetic data. In this paper, we investigated the joint petrophysical inversion (JPI) of shallow-seismic and multi-offset GPR data for more consistent imaging of near surface. As a bridge between the seismic parameters (P-wave velocity, S-wave velocity, and density) and GPR parameters (relative dielectric permittivity and electric conductivity), the petrophysical relationships with the parameters namely porosity and saturation are employed to link two data sets. We first did a sensitivity analysis of the petrophysical parameters to the seismic and GPR parameters and then determined an efficient integration of using shallow-seismic FWI to update porosity and GPR FWI to update saturation, respectively. A comparison of several parameterisation combinations shows that the seismic velocity parameterisation in shallow-seismic FWI and a modified logarithm parameterisation in GPR FWI works well in reconstructing reliable S-wave velocity and relative dielectric permittivity models, respectively. With the help from the petrophysical links, we realized JPI by transforming those well recovered parameters to the petrophysical parameters and then to other seismic and GPR parameters. A synthetic test indicates that, compared with the individual petrophysical inversion and individual FWI, JPI outperforms in simultaneously reconstructing all seismic, GPR, and petrophysical parameters with higher resolution and improved details. It is proved that JPI would be a potential data integration approach for the shallow subsurface investigation.</p>

scholarly journals S-wave experiments for the exploration of a deep geothermal carbonate reservoir in the German Molasse Basin

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Britta Wawerzinek ◽  
Hermann Buness ◽  
Hartwig von Hartmann ◽  
David C. Tanner
Keyword(s):  
Upper Jurassic ◽  
Carbonate Reservoir ◽  
P Wave ◽  
Seismic Survey ◽  
Seismic Exploration ◽  
Molasse Basin ◽  
S Wave ◽  
Induced Earthquakes ◽  
Conversion Point ◽  
Facies Classification

AbstractThere are many successful geothermal projects that exploit the Upper Jurassic aquifer at 2–3 km depth in the German Molasse Basin. However, up to now, only P-wave seismic exploration has been carried out. In an experiment in the Greater Munich area, we recorded S-waves that were generated by the conventional P-wave seismic survey, using 3C receivers. From this, we built a 3D volume of P- to S-converted (PS) waves using the asymptotic conversion point approach. By combining the P-volume and the resulting PS-seismic volume, we were able to derive the spatial distribution of the vp/vs ratio of both the Molasse overburden and the Upper Jurassic reservoir. We found that the vp/vs ratios for the Molasse units range from 2.0 to 2.3 with a median of 2.15, which is much higher than previously assumed. This raises the depth of hypocenters of induced earthquakes in surrounding geothermal wells. The vp/vs ratios found in the Upper Jurassic vary laterally between 1.5 and 2.2. Since no boreholes are available for verification, we test our results against an independently derived facies classification of the conventional 3D seismic volume and found it correlates well. Furthermore, we see that low vp/vs ratios correlate with high vp and vs velocities. We interpret the latter as dolomitized rocks, which are connected with enhanced permeability in the reservoir. We conclude that 3C registration of conventional P-wave surveys is worthwhile.

Numerical and Theoretical Investigation on the Origin of the Multiple Peaks of the H/V Ratio Curve

2021 ◽  
Author(s):  
Wanbo Xiao ◽  
Siqi Lu ◽  
Yanbin Wang
Keyword(s):  
Rayleigh Wave ◽  
Wave Velocity ◽  
Subsurface Layer ◽  
P Wave ◽  
Theoretical Formula ◽  
S Wave ◽  
Multiple Peaks ◽  
Ratio Curve ◽  
Multiple Layer ◽  
Wave Resonance

<p>Despite the popularity of the horizontal to vertical spectral ratio (HVSR) method in site effect studies, the origin of the H/V peaks has been controversial since this method was proposed. Many previous studies mainly focused on the explanation of the first or single peak of the H/V ratio, trying to distinguish between the two hypotheses — the S-wave resonance and ellipticity of Rayleigh wave. However, it is common both in numerical simulations and practical experiments that the H/V ratio exhibits multiple peaks, which is essential to explore the origin of the H/V peaks.</p><p>The cause for the multiple H/V peaks has not been clearly figured out, and once was simply explained as the result of multi subsurface layers. Therefore, we adopted numerical method to simulate the ambient noise in various layered half-space models and calculated the H/V ratio curves for further comparisons. The peak frequencies of the H/V curves accord well with the theoretical frequencies of S-wave resonance in two-layer models, whose frequencies only depend on the S wave velocity and the thickness of the subsurface layer. The same is true for models with varying model parameters. Besides, the theoretical formula of the S-wave resonance in multiple-layer models is proposed and then supported by numerical investigations as in the cases of two-layer models. We also extended the S-wave resonance to P-wave resonance and found that its theoretical frequencies fit well with the V/H peaks, which could be an evidence to support the S-wave resonance theory from a new perspective. By contrast, there are obvious differences between the higher orders of the H/V ratio peaks and the higher orders of Rayleigh wave ellipticity curves both in two-layer and multiple-layer models. The Rayleigh wave ellipticity curves are found to be sensitive to the Poisson’s ratio and the thickness of the subsurface layer, so the variation of the P wave velocity can affect the peak frequencies of the Rayleigh wave ellipticity curves while the H/V peaks show slight change. The Rayleigh wave ellipticity theory is thus proved to be inappropriate for the explanation of the multiple H/V peaks, while the possible effects of the Rayleigh wave on the fundamental H/V peak still cannot be excluded.</p><p>Based on the analyses above, we proposed a new evidence to support the claim that the peak frequencies of the H/V ratio curve, except the fundamental peaks, are caused by S-wave resonance. The relationship between the P-wave resonance and the V/H peaks may also find further application.</p>

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.

Constraints on the composition of the crust and uppermost mantle in northwestern Canada: Vp/Vs variations along Lithoprobe's SNorCLE transect

2005 ◽  
Vol 42 (6) ◽  
pp. 1205-1222 ◽  
Author(s):  
Gabriela Fernández-Viejo ◽  
Ron M Clowes ◽  
J Kim Welford
Keyword(s):  
Wave Velocity ◽  
Upper Mantle ◽  
Laboratory Data ◽  
High Ratio ◽  
P Wave ◽  
S Wave ◽  
Uppermost Mantle ◽  
Crust And Upper Mantle ◽  
Slave Craton ◽  
Crustal Composition

Shear-wave seismic data recorded along four profiles during the SNoRE 97 (1997 Slave – Northern Cordillera Refraction Experiment) refraction – wide-angle reflection experiment in northwestern Canada are analyzed to provide S-wave velocity (Vs) models. These are combined with previous P-wave velocity (Vp) models to produce cross sections of the ratio Vp/Vs for the crust and upper mantle. The Vp/Vs values are related to rock types through comparisons with published laboratory data. The Slave craton has low Vp/Vs values of 1.68–1.72, indicating a predominantly silicic crustal composition. Higher values (1.78) for the Great Bear and eastern Hottah domains of the Wopmay orogen imply a more mafic than average crustal composition. In the western Hottah and Fort Simpson arc, values of Vp/Vs drop to ∼1.69. These low values continue westward for 700 km into the Foreland and Omineca belts of the Cordillera, providing support for the interpretation from coincident seismic reflection studies that much of the crust from east of the Cordilleran deformation front to the Stikinia terrane of the Intermontane Belt consists of quartzose metasedimentary rocks. Stikinia shows values of 1.78–1.73, consistent with its derivation as a volcanic arc terrane. Upper mantle velocity and ratio values beneath the Slave craton indicate an ultramafic peridotitic composition. In the Wopmay orogen, the presence of low Vp/Vs ratios beneath the Hottah – Fort Simpson transition indicates the presence of pyroxenite in the upper mantle. Across the northern Cordillera, low Vp values and a moderate-to-high ratio in the uppermost mantle are consistent with the region's high heat flow and the possible presence of partial melt.

Nonlinear two‐dimensional elastic inversion of multioffset seismic data

Geophysics ◽  
1987 ◽  
Vol 52 (9) ◽  
pp. 1211-1228 ◽  
Author(s):  
Peter Mora
Keyword(s):  
Wave Equation ◽  
Wave Velocity ◽  
A Priori ◽  
Gaussian Model ◽  
Wave Impedance ◽  
P Wave ◽  
S Wave ◽  
Elastic Wave Equation ◽  
Gradient Direction ◽  
P Wave Velocity

The treatment of multioffset seismic data as an acoustic wave field is becoming increasingly disturbing to many geophysicists who see a multitude of wave phenomena, such as amplitude‐offset variations and shearwave events, which can only be explained by using the more correct elastic wave equation. Not only are such phenomena ignored by acoustic theory, but they are also treated as undesirable noise when they should be used to provide extra information, such as S‐wave velocity, about the subsurface. The problems of using the conventional acoustic wave equation approach can be eliminated via an elastic approach. In this paper, equations have been derived to perform an inversion for P‐wave velocity, S‐wave velocity, and density as well as the P‐wave impedance, S‐wave impedance, and density. These are better resolved than the Lamé parameters. The inversion is based on nonlinear least squares and proceeds by iteratively updating the earth parameters until a good fit is achieved between the observed data and the modeled data corresponding to these earth parameters. The iterations are based on the preconditioned conjugate gradient algorithm. The fundamental requirement of such a least‐squares algorithm is the gradient direction which tells how to update the model parameters. The gradient direction can be derived directly from the wave equation and it may be computed by several wave propagations. Although in principle any scheme could be chosen to perform the wave propagations, the elastic finite‐ difference method is used because it directly simulates the elastic wave equation and can handle complex, and thus realistic, distributions of elastic parameters. This method of inversion is costly since it is similar to an iterative prestack shot‐profile migration. However, it has greater power than any migration since it solves for the P‐wave velocity, S‐wave velocity, and density and can handle very general situations including transmission problems. Three main weaknesses of this technique are that it requires fairly accurate a priori knowledge of the low‐ wavenumber velocity model, it assumes Gaussian model statistics, and it is very computer‐intensive. All these problems seem surmountable. The low‐wavenumber information can be obtained either by a prior tomographic step, by the conventional normal‐moveout method, by a priori knowledge and empirical relationships, or by adding an additional inversion step for low wavenumbers to each iteration. The Gaussian statistics can be altered by preconditioning the gradient direction, perhaps to make the solution blocky in appearance like well logs, or by using large model variances in the inversion to reduce the effect of the Gaussian model constraints. Moreover, with some improvements to the algorithm and more parallel computers, it is hoped the technique will soon become routinely feasible.

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