Integrated Analysis of Core Geology, Rock Properties, Well Logs, and Seismic Data Provides a Well Constrained Geologic Model of the Bossier/Haynesville System

2013 ◽  
Author(s):  
Roberto Suarez-Rivera ◽  
Shanna Herring ◽  
David Handwerger ◽  
Sonia Marino ◽  
John Petriello ◽  
...  
Keyword(s):  
Seismic Data ◽  
Well Logs ◽  
Rock Properties ◽  
Integrated Analysis ◽  
Geologic Model

Integrated Analysis of Well Logs and Seismic Data for Reservoir Characterization to Estimate Hydrocarbon

2014 ◽  
Author(s):  
A. Kumar ◽  
W. Ismail Wan Yusoff ◽  
V. Sagayan a/l Asirvadam ◽  
S. Chandra Dass
Keyword(s):  
Seismic Data ◽  
Reservoir Characterization ◽  
Well Logs ◽  
Integrated Analysis

Reservoir properties prediction integrating controlled-source electromagnetic, prestack seismic, and well-log data using a rock-physics framework: Case study in the Hoop Area, Barents Sea, Norway

2017 ◽  
Vol 5 (2) ◽  
pp. SE43-SE60 ◽  
Author(s):  
Pedro Alvarez ◽  
Amanda Alvarez ◽  
Lucy MacGregor ◽  
Francisco Bolivar ◽  
Robert Keirstead ◽  
...  
Keyword(s):  
Seismic Data ◽  
Barents Sea ◽  
Rock Physics ◽  
Positive Outcome ◽  
Rock Properties ◽  
Integrated Analysis ◽  
Reservoir Properties ◽  
Data Set ◽  
Controlled Source ◽  
Rotation Scheme

We have developed an example from the Hoop Area of the Barents Sea showing a sequential quantitative integration approach to integrate seismic and controlled-source electromagnetic (CSEM) attributes using a rock-physics framework. The example illustrates a workflow to address the challenges of multiphysics and multiscale data integration for reservoir characterization purposes. A data set consisting of 2D GeoStreamer seismic and towed streamer electromagnetic data that were acquired concurrently in 2015 by PGS provide the surface geophysical measurements that we used. Two wells in the area — Wisting Central (7324/8-1) and Wisting Alternative (7324/7-1S) — provide calibration for the rock-physics modeling and the quantitative integrated analysis. In the first stage of the analysis, we invert prestack seismic and CSEM data separately for impedance and anisotropic resistivity, respectively. We then apply the multi-attribute rotation scheme (MARS) to estimate rock properties from seismic data. This analysis verified that the seismic data alone cannot distinguish between commercial and noncommercial hydrocarbon saturation. Therefore, in the final stage of the analysis, we invert the seismic and CSEM-derived properties within a rock-physics framework. The inclusion of the CSEM-derived resistivity information within the inversion approach allows for the separation of these two possible scenarios. Results reveal excellent correlation with known well outcomes. The integration of seismic, CSEM, and well data predicts very high hydrocarbon saturations at Wisting Central and no significant saturation at Wisting Alternative, consistent with the findings of each well. Two further wells were drilled in the area and used as blind tests in this case: The slightly lower saturation predicted at Hanssen (7324/7-2) is related to 3D effects in the CSEM data, but the positive outcome of the well is correctly predicted. At Bjaaland (7324/8-2), although the seismic indications are good, the integrated interpretation result predicts correctly that this well was unsuccessful.

Detailed quantitative sequence stratigraphic interpretation for the characterization of Amangi field using seismic data and well logs

2021 ◽  
Vol 19 (3) ◽  
pp. 63-82
Author(s):  
S. Inichinbia ◽  
Halidu Hamza
Keyword(s):  
Seismic Data ◽  
Gamma Ray ◽  
Hydrocarbon Exploration ◽  
Well Logs ◽  
Rock Properties ◽  
Sequence Stratigraphic ◽  
Resistivity Logs ◽  
Hydrocarbon Saturation ◽  
Shaly Sand ◽  
Net To Gross

The sequence stratigraphy of Amangi field of the Niger Delta was studied using seismic data and well logs. The field is a structurally  complex one and presents serious challenges to hydrocarbon exploration and production. The main objective of these analyses is to  identify sand intervals using the available data. Well log data were used as additional tools to constrain the seismic correlations in order to solve the correlation problem. The well logs were evaluated for the field’s petrophysical properties by combining the gamma ray and resistivity logs to determine reservoir zones with considerable hydrocarbon saturation. Also, the relationship between some basic rock properties/attributes and litho-types were determined for the study area. Next, well-to-seismic ties were produced and two horizons were picked. Acoustic impedance inversion was also performed which revealed “hard sands” due to mixed lithologies (heterolithics). This made it difficult to discriminate the sands from shales in the P-impedance domain alone. So, progress was made to determine the net-to-gross of the field. The analysis revealed that these reservoirs have shaly sand with shale content of 10%, porosity averaging 21%, and hydrocarbon saturation of 90%. The result established a vertical stack of a series of reservoirs in an anticlinal structure of which the H1000 and H4000 stand out for their huge volumes of rich gas condensate accumulation. This discovery provoked the drive for the first phase of development of this field. Keywords: stratigraphy, facies, net-to-gross, horizon, lithology, well-to-seismic tie, impedance

Integrated Analysis of Well Logs and Seismic Data to Deduce the Possible Distribution in Depth of Gas Hydrate in Shenhu Area, South China Sea

2014 ◽  
Vol 57 (5) ◽  
pp. 761-770
Author(s):  
XU Hua-Ning ◽  
ZHANG Guang-Xue ◽  
ZHENG Xiao-Dong ◽  
WANG Ming-Jun ◽  
YANG Sheng-Xiong ◽  
...  
Keyword(s):  
South China Sea ◽  
South China ◽  
Gas Hydrate ◽  
Seismic Data ◽  
Well Logs ◽  
Integrated Analysis ◽  
Shenhu Area ◽  
China Sea

Integrated Analysis of Borehole and Surface Seismic Data to Resolve Seismic Uncertainties in the Gulf Of Suez

2014 ◽  
Author(s):  
Mohamed S El-Hateel ◽  
Parvez Ahmad ◽  
Ahmed Hesham A Ismail ◽  
Islam A M Henaish ◽  
Ahmed Ashraf
Keyword(s):  
Seismic Data ◽  
Integrated Analysis ◽  
Gulf Of Suez

Stochastic discrete fracture network modeling in shale reservoirs via integration of seismic attributes and petrophysical data

2021 ◽  
pp. 1-50
Author(s):  
Yongchae Cho
Keyword(s):  
Seismic Data ◽  
Stochastic Approach ◽  
Fracture Network ◽  
Natural Fracture ◽  
Well Logs ◽  
Fracture Model ◽  
Well Log ◽  
Discrete Fracture ◽  
Discrete Fracture Network Modeling ◽  
Fracture Network Modeling

The prediction of natural fracture networks and their geomechanical properties remains a challenge for unconventional reservoir characterization. Since natural fractures are highly heterogeneous and sub-seismic scale, integrating petrophysical data (i.e., cores, well logs) with seismic data is important for building a reliable natural fracture model. Therefore, I introduce an integrated and stochastic approach for discrete fracture network modeling with field data demonstration. In the proposed method, I first perform a seismic attribute analysis to highlight the discontinuity in the seismic data. Then, I extrapolate the well log data which includes localized but high-confidence information. By using the fracture intensity model including both seismic and well logs, I build the final natural fracture model which can be used as a background model for the subsequent geomechanical analysis such as simulation of hydraulic fractures propagation. As a result, the proposed workflow combining multiscale data in a stochastic approach constructs a reliable natural fracture model. I validate the constructed fracture distribution by its good agreement with the well log data.

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