scholarly journals Petrophysical seismic inversion based on lithofacies classification to enhance reservoir properties estimation: a machine learning approach

2020 ◽  
Author(s):  
Amir Abbas Babasafari ◽  
Shiba Rezaei ◽  
Ahmed Mohamed Ahmed Salim ◽  
Sayed Hesammoddin Kazemeini ◽  
Deva Prasad Ghosh
Keyword(s):  
Acoustic Impedance ◽  
Reservoir Characterization ◽  
Seismic Inversion ◽  
Reservoir Properties ◽  
Well Location ◽  
The Neural Network ◽  
Machine Learning Approach ◽  
Lithofacies Classification ◽  
Elastic Inversion ◽  
Significant Match

Abstract For estimation of petrophysical properties in industry, we are looking for a methodology which results in more accurate outcome and also can be validated by means of some quality control steps. To achieve that, an application of petrophysical seismic inversion for reservoir properties estimation is proposed. The main objective of this approach is to reduce uncertainty in reservoir characterization by incorporating well log and seismic data in an optimal manner. We use nonlinear optimization algorithms in the inversion workflow to estimate reservoir properties away from the wells. The method is applied at well location by fitting nonlinear experimental relations on the petroelastic cross-plot, e.g., porosity versus acoustic impedance for each lithofacies class separately. Once a significant match between the measured and the predicted reservoir property is attained in the inversion workflow, the petrophysical seismic inversion based on lithofacies classification is applied to the inverted elastic property, i.e., acoustic impedance or Vp/Vs ratio derived from seismic elastic inversion to predict the reservoir properties between the wells. Comparison with the neural network method demonstrated this application of petrophysical seismic inversion to be competitive and reliable.

A Novel Approach for a better exploitation of a 3D seismic on a development field 

2021 ◽  
Author(s):  
Nasrine Medjdouba ◽  
Zahia Benaissa ◽  
Sabiha Annou
Keyword(s):  
Reservoir Characterization ◽  
Seismic Analysis ◽  
Lower Triassic ◽  
Seismic Inversion ◽  
Reservoir Properties ◽  
Seismic Attribute ◽  
Amplitude Inversion ◽  
Well Location ◽  
Attribute Analysis ◽  
Novel Approach

<p>The main hydrocarbon-bearing reservoirover the study area is the lower Triassic Argilo-Gréseux reservoir. The Triassic sand is deposited as fluvial channels and overbank sands with a thickness ranging from 10 to 20 m, lying unconformably on the Paleozoic formations. Lateral and vertical distribution of the sand bodies is challenging which makes their mapping very difficult andnearly impossible with conventional seismic analysis. </p><p>In order to better define the optimum drilling targets, the seismic attribute analysis and reservoir characterization process were performed targeting suchthin reservoir level, analysis of available two seismic vintages of PSTM cubes as well as post and pre stack inversion results were carried out.The combination of various attributes analysis (RMS amplitude, Spectral decomposition, variance, etc.) along with seismic inversion results has helped to clearly identify the channelized feature and its delineation on various horizon slices and geobodies, the results were reviewed and calibrated with reservoir properties at well location and showed remarkable correlation.</p><p>Ten development wells have been successfully drilledbased on the seismic analysis study, confirming the efficiency of seismic attribute analysis to predicted channel body geometry.</p><p>Keywords: Channel, Attributes, Amplitude, Inversion, Fluvial reservoir.</p>

Applications of quantitative prestack seismic analysis to unconventional resource play characterization in the Permian/Delaware Basin

2019 ◽  
Vol 38 (2) ◽  
pp. 106-115 ◽  
Author(s):  
Phuong Hoang ◽  
Arcangelo Sena ◽  
Benjamin Lascaud
Keyword(s):  
Hydraulic Fracturing ◽  
Seismic Data ◽  
Reservoir Characterization ◽  
Seismic Analysis ◽  
Seismic Inversion ◽  
Reservoir Properties ◽  
Yield Attributes ◽  
Horizontal Drilling ◽  
Delaware Basin ◽  
Unconventional Resource

The characterization of shale plays involves an understanding of tectonic history, geologic settings, reservoir properties, and the in-situ stresses of the potential producing zones in the subsurface. The associated hydrocarbons are generally recovered by horizontal drilling and hydraulic fracturing. Historically, seismic data have been used mainly for structural interpretation of the shale reservoirs. A primary benefit of surface seismic has been the ability to locate and avoid drilling into shallow carbonate karsting zones, salt structures, and basement-related major faults which adversely affect the ability to drill and complete the well effectively. More recent advances in prestack seismic data analysis yield attributes that appear to be correlated to formation lithology, rock strength, and stress fields. From these, we may infer preferential drilling locations or sweet spots. Knowledge and proper utilization of these attributes may prove valuable in the optimization of drilling and completion activities. In recent years, geophysical data have played an increasing role in supporting well planning, hydraulic fracturing, well stacking, and spacing. We have implemented an integrated workflow combining prestack seismic inversion and multiattribute analysis, microseismic data, well-log data, and geologic modeling to demonstrate key applications of quantitative seismic analysis utilized in developing ConocoPhillips' acreage in the Delaware Basin located in Texas. These applications range from reservoir characterization to well planning/execution, stacking/spacing optimization, and saltwater disposal. We show that multidisciplinary technology integration is the key for success in unconventional play exploration and development.

Introduction to this special section: Rock physics

2019 ◽  
Vol 38 (5) ◽  
pp. 332-332
Author(s):  
Yongyi Li ◽  
Lev Vernik ◽  
Mark Chapman ◽  
Joel Sarout
Keyword(s):  
Reservoir Characterization ◽  
Model Building ◽  
Seismic Analysis ◽  
Focal Point ◽  
Special Section ◽  
Rock Physics ◽  
Seismic Inversion ◽  
Reservoir Properties ◽  
Model Studies ◽  
Experimental Rock

Rock physics links the physical properties of rocks to geophysical and petrophysical observations and, in the process, serves as a focal point in many exploration and reservoir characterization studies. Today, the field of rock physics and seismic petrophysics embraces new directions with diverse applications in estimating static and dynamic reservoir properties through time-variant mechanical, thermal, chemical, and geologic processes. Integration with new digital and computing technologies is gradually gaining traction. The use of rock physics in seismic imaging, prestack seismic analysis, seismic inversion, and geomechanical model building also contributes to the increase in rock-physics influence. This special section highlights current rock-physics research and practices in several key areas, namely experimental rock physics, rock-physics theory and model studies, and the use of rock physics in reservoir characterizations.

Integrated workflow approach to static modeling of Igloo R3 reservoir, onshore Niger Delta, Nigeria

2015 ◽  
Vol 3 (3) ◽  
pp. SZ1-SZ14 ◽  
Author(s):  
Emmanuel Kenechukwu Anakwuba ◽  
Clement Udenna Onyekwelu ◽  
Augustine Ifeanyi Chinwuko
Keyword(s):  
Correlation Coefficient ◽  
Acoustic Impedance ◽  
Niger Delta ◽  
Seismic Inversion ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Sequential Gaussian Simulation ◽  
Reservoir Properties ◽  
Static Modeling ◽  
Geophysical Well Logs

We constructed a 3D static model of the R3 reservoir at the Igloo Field, Onshore Niger Delta, by integrating the 3D seismic volume, geophysical well logs, and core petrophysical data. In this model, we used a combined petrophysical-based reservoir zonation and geostatistical inversion of seismic attributes to reduce vertical upscaling problems and improve the estimation of reservoir properties between wells. The reservoir structural framework was interpreted to consist of three major synthetic faults; two of them formed northern and southern boundaries of the field, whereas the other one separated the field into two hydrocarbon compartments. These compartments were pillar gridded into 39,396 cells using a [Formula: see text] dimension over an area of [Formula: see text]. Analysis of the field petrophysical distribution showed an average of 21% porosity, 34% volume of shale, and 680-mD permeability. Eleven flow units delineated from a stratigraphic modified Lorenz plot were used to define the reservoir’s stratigraphic framework. The calibration of acoustic impedance using sonic- and density-log porosity showed a 0.88 correlation coefficient; this formed the basis for the geostatistic seismic inversion process. The acoustic impedance was transformed into reservoir parameters using a sequential Gaussian simulation algorithm with collocated cokriging and variogram models. Ten equiprobable acoustic impedance models were generated and further converted into porosity models by using their bivariate relationship. We modeled the permeability with a single transform of core porosity with a correlation coefficient of 0.86. We compared an alternative model of porosity without seismic as a secondary control, and the result showed differences in their spatial distributions, which was a major control to fluid flow. However, there were similarities in their probability distribution functions and cumulative distribution functions.

scholarly journals Integrated Well Data And 3D Seismic Inversion Study For Reservoir Delineation And Description

2020 ◽  
Vol 70 (1) ◽  
pp. 209-220
Author(s):  
Qazi Sohail Imran ◽  
◽  
Numair Ahmad Siddiqui ◽  
Abdul Halim Abdul Latif ◽  
Yasir Bashir ◽  
...  
Keyword(s):  
Reservoir Characterization ◽  
Rock Physics ◽  
Seismic Inversion ◽  
Depositional Environments ◽  
Well Log ◽  
Reservoir Properties ◽  
Rock Physics Modeling ◽  
Physics Modeling ◽  
And Performance ◽  
Well Log Analysis

Offshore petroleum systems are often very complex and subtle because of a variety of depositional environments. Characterizing a reservoir based on conventional seismic and well-log stratigraphic analysis in intricate settings often leads to uncertainties. Drilling risks, as well as associated subsurface uncertainties can be minimized by accurate reservoir delineation. Moreover, a forecast can also be made about production and performance of a reservoir. This study is aimed to design a workflow in reservoir characterization by integrating seismic inversion, petrophysics and rock physics tools. Firstly, to define litho facies, rock physics modeling was carried out through well log analysis separately for each facies. Next, the available subsurface information is incorporated in a Bayesian engine which outputs several simulations of elastic reservoir properties, as well as their probabilities that were used for post-inversion analysis. Vast areal coverage of seismic and sparse vertical well log data was integrated by geostatistical inversion to produce acoustic impedance realizations of high-resolution. Porosity models were built later using the 3D impedance model. Lastly, reservoir bodies were identified and cross plot analysis discriminated the lithology and fluid within the bodies successfully.

scholarly journals Seismic Interpretation and Inversion Leading to an Accurate Reservoir Characterization in a Carbonate Environment

2021 ◽  
Vol 2 (12) ◽  
pp. 1229-1230
Author(s):  
Yasir Bashir ◽  
Nordiana Mohd Muztaza ◽  
Nur Azwin Ismail ◽  
Ismail Ahmad Abir ◽  
Andy Anderson Bery ◽  
...  
Keyword(s):  
Seismic Data ◽  
Acoustic Impedance ◽  
Reservoir Characterization ◽  
Rock Physics ◽  
Seismic Inversion ◽  
Seismic Interpretation ◽  
And Inversion

Seismic data acquired in the field show the subsurface reflectors or horizon among the geological strata, while the seismic inversion converts this reflector information into the acoustic impedance section which shows the layer properties based on lithology. The research aims to predict the porosity to identify the reservoir which is in between the tight layer. So, the output of the seismic inversion is much more batter than the seismic as it is closer to reality such as geology. Seismic inversion is frequently used to determine rock physics properties, for example, acoustic impedance and porosity.

Integration of broadband seismic data into reservoir characterization workflows: A case study from the Campos Basin, Brazil

2018 ◽  
Vol 6 (1) ◽  
pp. T145-T161 ◽  
Author(s):  
Ekaterina Kneller ◽  
Manuel Peiro
Keyword(s):  
Reservoir Characterization ◽  
Petroleum Exploration ◽  
Full Potential ◽  
Reservoir Properties ◽  
Data Set ◽  
Low Frequencies ◽  
Campos Basin ◽  
Elastic Inversion

Towed-streamer marine broadband data have been key contributors to recent petroleum exploration history, in new frontiers and in mature basins around the world. They have improved the characterization of reservoirs by reducing the uncertainty in structural and stratigraphic interpretation and by providing more quantitative estimates of reservoir properties. Dedicated acquisition, processing, and quality control (QC) methods have been developed to capitalize on the broad bandwidth of the data and allow their rapid integration into reservoir models. Using a variable-depth steamer data set acquired in the Campos Basin, Brazil, we determine that particular care that should be taken when processing and inverting broadband data to realize their full potential for reservoir interpretation and uncertainty management in the reservoir model. In particular, we determine the QC implemented and interpretative processing approach used to monitor data improvements during processing and preconditioning for elastic inversion. In addition, we evaluate the importance of properly modeling the low frequencies during wavelet estimation. We find the benefits of carefully processed broadband data for structural interpretation and describe the application of acoustic and elastic inversions cascaded with Bayesian lithofacies classification, to provide clear interpretative products with which we were able to demonstrate a reduction in the uncertainty of the prediction and characterization of Santonian oil sandstones in the Campos Basin.

Integrated reservoir characterization of a Utica Shale with focus on sweet spot discrimination

2020 ◽  
Vol 8 (3) ◽  
pp. SM1-SM14
Author(s):  
Jinming Zhu
Keyword(s):  
Reservoir Characterization ◽  
Water Saturation ◽  
Clay Content ◽  
Seismic Inversion ◽  
Reservoir Properties ◽  
Geomechanical Properties ◽  
Utica Shale ◽  
Characterization Study ◽  
Separate Point

Multiclient 3D seismic data were acquired in 2015 in eastern Ohio for reservoir characterization of the Utica Shale consisting of the Utica and Point Pleasant Formations. I attained accurate, high-fidelity acoustic impedance, shear impedance, density, and [Formula: see text], from elastic inversion. These accurate inversion results allow consistent calculation of reservoir and geomechanical properties of the Utica Shale. I found density critically important affecting the accuracy of other reservoir and geomechanical properties. More than a dozen properties in geologic, geomechanical, and reservoir categories were acquired from logs, cores, and seismic inversion, for this integrated reservoir characterization study. These properties include buried depth, formation thickness, mineralogy, density, Young’s modulus, Poisson’s ratio (PR), brittleness, total organic carbon (TOC), porosity, water saturation, permeability, clay content, and natural fractures. A ternary diagram of core samples from 18 wells demonstrates that the Point Pleasant is dominant with calcite, whereas the Utica mainly contains clay. Inverted density clearly divides Point Pleasant as low density from the overlying Utica. Calculated reservoir properties undoubtedly delineate the traditional Utica Shale as two distinctive formations. I calculated that the Utica Formation contains 1%–2% TOC, 3.5%–4.8% porosity, 10%–24% water saturation, and 40%–58% clay content, whereas Point Pleasant contains 3%–4.5% TOC, 5%–9% porosity, 2%–10% water saturation, and 15%–35% clay content. The PR and brittleness clearly separate Point Pleasant from the overlying Utica, with a lower PR and a higher brittleness index in Point Pleasant than in Utica. The higher brittleness in Point Pleasant makes it easier to frac, leading to enhanced permeability. Both formations exhibit spatial variations of reservoir and geomechanical properties. Nevertheless, the underlying Point Pleasant is obviously better than the Utica Shale with favorable reservoir and geomechanical properties for optimal development and production, although Utica is thicker and shallower. The central and southeastern portions of Point Pleasant have the sweetest reservoirs.

scholarly journals Application of the Acoustic Impedance (AI) Seismic Inversion and Multi-Attribute Method for Reservoir Characterization in Bonaparte Basin

2021 ◽  
Vol 4 (1) ◽  
pp. 8-20
Author(s):  
Maurin Puspitasari ◽  
Ambran Hartono ◽  
Egie Wijaksono ◽  
Tati Zera
Keyword(s):  
Acoustic Impedance ◽  
Stepwise Regression ◽  
Reservoir Characterization ◽  
Seismic Inversion ◽  
Impedance Method ◽  
Linear Regression Method ◽  
Seismic Method ◽  
Impedance Inversion ◽  
Southwest Part ◽  
Acoustic Impedance Method

Research on the application of the acoustic impedance (AI) seismic inversion and multi-attribute method was conducted with the aim to characterize the reservoir in the Bonaparte Basin. The modeling which used in the acoustic impedance inversion seismic method is model-based. Meanwhile, the multi-attribute seismic method used log porosity that appliying the linear regression method and using the stepwise regression technique. Based on the result of the sensitivity analysis and analysis using the seismic inversion acoustic impedance method, the sandstone reservoir zone that has the prospect of hydrocarbons containing gas is located in the Northeast-Southwest part of the study area which in WCB-1, WCB-3 and WCB-4 well with the acoustic impedance values are in the range of 4,800 - 13,000 (m / s) * (g / cc), and the porosity values generated from the analysis using the multi-attribute seismic method are in the range of 5 - 16% in WCB-1 and WCB-4, 2 - 10% on WCB-3.

Sign in / Sign up

Export Citation Format

Share Document