Study of Geostatistical Inversion in the Lithologic Distribution and Velocity Modeling of Thick Igneous Rock in the FY Area, Northern Tarim Basin, China

2021 ◽  
Author(s):  
Y. Xu ◽  
H. Yang ◽  
G. Peng ◽  
X. Deng ◽  
Q. Miao ◽  
...  
Keyword(s):  
High Precision ◽  
Tarim Basin ◽  
Velocity Model ◽  
Igneous Rocks ◽  
Inversion Method ◽  
Velocity Modeling ◽  
Migration Imaging ◽  
Lithology Identification ◽  
Geostatistical Inversion ◽  
Northern Tarim Basin

Abstract In the northern Tarim Basin, a large number of thick igneous rocks are encountered in the drilling process in the Permian. Their lithology and velocity are very strongly, which has a great influence on migration imaging of the “beaded” areas. It is very important to conduct the fine lithology identification and high-precision velocity modeling of the igneous rocks for the exploration and development of the reservoirs. A geostatistical inversion method to obtain the igneous-rock lithologic distribution pattern and velocity modeling in the FY area of the northern Tarim Basin is introduced in this paper. The results show that the application of the geostatistical inversion method greatly improves the resolution of lithology identification. This helps us further understand the Permian igneous rocks distribution in the FY area. Comparison between the seismic facies classification maps of the FY study area shows that the obtained velocity model can reflect the lateral distribution of igneous rocks well. At the same time, the velocity model can reflect the variation of igneous rocks velocity in detail and has a high precision. The average velocity error of the wells participating in the inversion is less than 2%, and the minimum average velocity error is 0.23%. Finally, the velocity model is applied to seismic data processing, and the processing results indicate that it can help to improve seismic migration imaging. The study demonstrates that the geostatistical inversion method can provide a high-precision velocity model for formation pressure prediction and seismic data processing and interpretation, ultimately guiding the exploration and development of oil.

First-arrival traveltime inversion of seismic diving waves observed on undulant surface

2021 ◽  
Vol 225 (2) ◽  
pp. 1020-1031
Author(s):  
Huachen Yang ◽  
Jianzhong Zhang ◽  
Kai Ren ◽  
Changbo Wang
Keyword(s):  
Turning Points ◽  
Analytical Formula ◽  
Velocity Model ◽  
Western China ◽  
Inversion Method ◽  
Mountain Area ◽  
Traveltime Inversion ◽  
Static Correction ◽  
Velocity Models ◽  
First Arrival

SUMMARY A non-iterative first-arrival traveltime inversion method (NFTI) is proposed for building smooth velocity models using seismic diving waves observed on irregular surface. The new ray and traveltime equations of diving waves propagating in smooth media with undulant observation surface are deduced. According to the proposed ray and traveltime equations, an analytical formula for determining the location of the diving-wave turning points is then derived. Taking the influence of rough topography on first-arrival traveltimes into account, the new equations for calculating the velocities at turning points are established. Based on these equations, a method is proposed to construct subsurface velocity models from the observation surface downward to the bottom using the first-arrival traveltimes in common offset gathers. Tests on smooth velocity models with rugged topography verify the validity of the established equations, and the superiority of the proposed NFTI. The limitation of the proposed method is shown by an abruptly-varying velocity model example. Finally, the NFTI is applied to solve the static correction problem of the field seismic data acquired in a mountain area in the western China. The results confirm the effectivity of the proposed NFTI.

scholarly journals High-Precision Soil Moisture Mapping Based on Multi-Model Coupling and Background Knowledge, Over Vegetated Areas Using Chinese GF-3 and GF-1 Satellite Data

2020 ◽  
Vol 12 (13) ◽  
pp. 2123 ◽  
Author(s):  
Leran Han ◽  
Chunmei Wang ◽  
Tao Yu ◽  
Xingfa Gu ◽  
Qiyue Liu
Keyword(s):  
Soil Moisture ◽  
High Precision ◽  
Satellite Data ◽  
Solution Method ◽  
Pearson Correlation ◽  
Optimal Solution ◽  
Background Knowledge ◽  
Optical Data ◽  
Inversion Method ◽  
Synthetic Aperture Radar Data

This paper proposes a combined approach comprising a set of methods for the high-precision mapping of soil moisture in a study area located in Jiangsu Province of China, based on the Chinese C-band synthetic aperture radar data of GF-3 and high spatial-resolution optical data of GF-1, in situ experimental datasets and background knowledge. The study was conducted in three stages: First, in the process of eliminating the effect of vegetation canopy, an empirical vegetation water content model and a water cloud model with localized parameters were developed to obtain the bare soil backscattering coefficient. Second, four commonly used models (advanced integral equation model (AIEM), look-up table (LUT) method, Oh model, and the Dubois model) were coupled to acquire nine soil moisture retrieval maps and algorithms. Finally, a simple and effective optimal solution method was proposed to select and combine the nine algorithms based on classification strategies devised using three types of background knowledge. A comprehensive evaluation was carried out on each soil moisture map in terms of the root-mean-square-error (RMSE), Pearson correlation coefficient (PCC), mean absolute error (MAE), and mean bias (bias). The results show that for the nine individual algorithms, the estimated model constructed using the AIEM (mv1) was significantly more accurate than those constructed using the other models (RMSE = 0.0321 cm³/cm³, MAE = 0.0260 cm³/cm³, and PCC = 0.9115), followed by the Oh model (m_v5) and LUT inversion method under HH polarization (mv2). Compared with the independent algorithms, the optimal solution methods have significant advantages; the soil moisture map obtained using the classification strategy based on the percentage content of clay was the most satisfactory (RMSE = 0.0271 cm³/cm³, MAE = 0.0225 cm³/cm³, and PCC = 0.9364). This combined method could not only effectively integrate the optical and radar satellite data but also couple a variety of commonly used inversion models, and at the same time, background knowledge was introduced into the optimal solution method. Thus, we provide a new method for the high-precision mapping of soil moisture in areas with a complex underlying surface.

Traveltime information-based wave-equation inversion

Geophysics ◽  
2009 ◽  
Vol 74 (6) ◽  
pp. WCC27-WCC36 ◽  
Author(s):  
Yu Zhang ◽  
Daoliu Wang
Keyword(s):  
Wave Equation ◽  
Conventional Method ◽  
Seismic Data ◽  
Waveform Inversion ◽  
Back Propagation ◽  
Velocity Model ◽  
Data Fitting ◽  
Inversion Method ◽  
New Wave ◽  
Seismic Record

We propose a new wave-equation inversion method that mainly depends on the traveltime information of the recorded seismic data. Unlike the conventional method, we first apply a [Formula: see text] transform to the seismic data to form the delayed-shot seismic record, back propagate the transformed data, and then invert the velocity model by maximizing the wavefield energy around the shooting time at the source locations. Data fitting is not enforced during the inversion, so the optimized velocity model is obtained by best focusing the source energy after a back propagation. Therefore, inversion accuracy depends only on the traveltime information embedded in the seismic data. This method may overcome some practical issues of waveform inversion; in particular, it relaxes the dependency of the seismic data amplitudes and the source wavelet.

Determination of oil charge timing in the Ordovician carbonate reservoir of the Tahe Oilfield, Tarim Basin, NW China

2021 ◽  
Author(s):  
Jiaxu Chen ◽  
Xiaowen Guo
Keyword(s):  
Tarim Basin ◽  
Sedimentary Basins ◽  
Carbonate Reservoir ◽  
Rock Interaction ◽  
Tahe Oilfield ◽  
Petroleum Systems ◽  
Calcite Veins ◽  
Homogenization Temperatures ◽  
Two Phases ◽  
Northern Tarim Basin

<p>Determining the timings of oil charge in sedimentary basins are essential to understand the evolutionary histories of petroleum systems, especially in sedimentary basins with complicated tectonic evolution and thermal histories. The Ordovician carbonate reservoir in the Tahe Oilfield, which is located in the northern Tarim Basin, comprises the largest marine reservoirs in China with reserves up to 3.2×10<sup>8</sup> t. This study aims to determine the timings of oil charge in the Ordovician carbonate reservoir in the Tahe Oilfield, Tarim Basin, which basin is subjected to multiple phases of tectonic deformations and oil charge. The phases of calcite veins that contain oil inclusions were systematically investigated by cathodoluminescence observation, in situ rare earth element, C, O, and Sr isotope analyses. The homogenization temperatures of aqueous inclusions that are coeval with oil inclusions were measured to determine the timings of oil charge by combining the burial and geothermal histories. Two phases of calcite veins were judged by the differences in cathodoluminescence color, Ce anomaly, δ<sup>18</sup>O, and <sup>87</sup>Sr/<sup>86</sup>Sr values, which might be caused by variations in the water-rock interaction processes during different calcite phases. Primary oil inclusions with yellow fluorescence were observed in the two phases of calcite veins, suggesting two phases of oil charge. By combining the homogenization temperatures of aqueous inclusions with the burial and geothermal histories, the timing of phase I oil charge was inferred to be 336–312 Ma, and the timing of phase II oil charge was inferred to be 237–217 Ma.</p>

Nonlinear velocity inversion by a two‐step Monte Carlo method.

Geophysics ◽  
1994 ◽  
Vol 59 (4) ◽  
pp. 577-590 ◽  
Author(s):  
Side Jin ◽  
Raul Madariaga
Keyword(s):  
Monte Carlo ◽  
Velocity Model ◽  
Small Scale ◽  
Inversion Method ◽  
Nonlinear Inversion ◽  
Ray Theory ◽  
Data Set ◽  
Seismic Reflection Data ◽  
Velocity Models ◽  
Reference Velocity

Seismic reflection data contain information on small‐scale impedance variations and a smooth reference velocity model. Given a reference velocity model, the reflectors can be obtained by linearized migration‐inversion. If the reference velocity is incorrect, the reflectors obtained by inverting different subsets of the data will be incoherent. We propose to use the coherency of these images to invert for the background velocity distribution. We have developed a two‐step iterative inversion method in which we separate the retrieval of small‐scale variations of the seismic velocity from the longer‐period reference velocity model. Given an initial background velocity model, we use a waveform misfit‐functional for the inversion of small‐scale velocity variations. For this linear step we use the linearized migration‐inversion method based on ray theory that we have recently developed with Lambaré and Virieux. The reference velocity model is then updated by a Monte Carlo inversion method. For the nonlinear inversion of the velocity background, we introduce an objective functional that measures the coherency of the short wavelength components obtained by inverting different common shot gathers at the same locations. The nonlinear functional is calculated directly in migrated data space to avoid expensive numerical forward modeling by finite differences or ray theory. Our method is somewhat similar to an iterative migration velocity analysis, but we do an automatic search for relatively large‐scale 1-D reference velocity models. We apply the nonlinear inversion method to a marine data set from the North Sea and also show that nonlinear inversion can be applied to realistic scale data sets to obtain a laterally heterogeneous velocity model with a reasonable amount of computer time.

Using orthorhombic depth imaging to image fractures in tight reservoirs of the RDG Field, Barmer Basin, India

2019 ◽  
Vol 38 (4) ◽  
pp. 268-273
Author(s):  
Maheswara Phani ◽  
Sushobhan Dutta ◽  
Kondal Reddy ◽  
Sreedurga Somasundaram
Keyword(s):  
Seismic Data ◽  
Velocity Model ◽  
Substantial Improvement ◽  
Natural Fractures ◽  
Data Set ◽  
Depth Migration ◽  
Velocity Modeling ◽  
Barmer Basin ◽  
Induced Fractures

Raageshwari Deep Gas (RDG) Field is situated in the southern part of the Barmer Basin in Rajasthan, India, at a depth of 3000 m. With both clastic and volcanic lithologies, the main reservoirs are tight, and hydraulic fracturing is required to enhance productivity, especially to improve permeability through interaction of induced fractures with natural fractures. Therefore, optimal development of the RDG Field reservoirs requires characterization of faults and natural fractures. To address this challenge, a wide-azimuth 3D seismic data set over the RDG Field was processed to sharply define faults and capture anisotropy related to open natural fractures. Anisotropy was indicated by the characteristic sinusoidal nature of gather reflection events processed using conventional tilted transverse imaging (TTI); accordingly, we used orthorhombic imaging to correct for these, to quantify fracture-related anisotropy, and to yield a more correct subsurface image. During prestack depth migration (PSDM) processing of the RDG data, TTI and orthorhombic velocity modeling was done with azimuthal sectoring of reflection arrivals. The resultant PSDM data using this velocity model show substantial improvement in image quality and vertical resolution at the reservoir level compared to vintage seismic data. The improved data quality enabled analysis of specialized seismic attributes like curvature and thinned fault likelihood for more reliable characterization of faults and fractures. These attributes delineate the location and distribution of probable fracture networks within the volcanic reservoirs. Interpreted subtle faults, associated with fracture zones, were validated with microseismic, production, and image log data.

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