Synergistic integration of seismic and geologic data for modeling petrophysical properties

2020 ◽  
Vol 39 (3) ◽  
pp. 164-169
Author(s):  
Yuan Zee Ma ◽  
David Phillips ◽  
Ernest Gomez
Keyword(s):  
Neural Networks ◽  
Seismic Data ◽  
Reservoir Characterization ◽  
Integrated Approach ◽  
Reservoir Modeling ◽  
Petrophysical Properties ◽  
Reservoir Properties ◽  
Field Development ◽  
Realistic Description ◽  
Geologic Data

Reservoir characterization and modeling have become increasingly important for optimizing field development. Optimal valuation and exploitation of a field requires a realistic description of the reservoir, which, in turn, requires integrated reservoir characterization and modeling. An integrated approach for reservoir modeling bridges the traditional disciplinary divides and tears down interdisciplinary barriers, leading to better handling of uncertainties and improvement of the reservoir model for field development. This article presents the integration of seismic data using neural networks and the incorporation of a depositional model and seismic data in constructing reservoir models of petrophysical properties. Some challenging issues, including low correlation due to Simpson's paradox and under- or overfitting of neural networks, are mitigated in geostatistical analysis and modeling of reservoir properties by integrating geologic information. This article emphasizes the integration of well logs, seismic prediction, and geologic data in the 3D reservoir-modeling workflow.

scholarly journals An Integrated Microfacies and Well Logs-Based Reservoir Characterization of Yamama Formation, Southern Iraq

2021 ◽  
pp. 3570-3586
Author(s):  
Mohanad M. Al-Ghuribawi ◽  
Rasha F. Faisal
Keyword(s):  
Reservoir Characterization ◽  
Water Saturation ◽  
Effective Porosity ◽  
Well Logs ◽  
Petrophysical Properties ◽  
Reservoir Properties ◽  
Thin Sections ◽  
Porosity And Permeability ◽  
South Of Iraq ◽  
Southern Iraq

     The Yamama Formation includes important carbonates reservoir that belongs to the Lower Cretaceous sequence in Southern Iraq. This study covers two oil fields (Sindbad and Siba) that are distributed Southeastern Basrah Governorate, South of Iraq. Yamama reservoir units were determined based on the study of cores, well logs, and petrographic examination of thin sections that required a detailed integration of geological data and petrophysical properties. These parameters were integrated in order to divide the Yamama Formation into six reservoir units (YA0, YA1, YA2, YB1, YB2 and YC), located between five cap rock units. The best facies association and petrophysical properties were found in the shoal environment, where the most common porosity types were the primary (interparticle) and secondary (moldic and vugs) . The main diagenetic process that occurred in YA0, YA2, and YB1 is cementation, which led to the filling of pore spaces by cement and subsequently decreased the reservoir quality (porosity and permeability). Based on the results of the final digital  computer interpretation and processing (CPI) performed by using the Techlog software, the units YA1 and YB2 have the best reservoir properties. The unit YB2 is characterized by a good effective porosity average, low water saturation, good permeability, and large thickness that distinguish it from other reservoir units.

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.

Novel fracture zone identifier attribute using geophysical and well log data for unconventional reservoirs

2015 ◽  
Vol 3 (3) ◽  
pp. T155-T167 ◽  
Author(s):  
Debotyam Maity ◽  
Fred Aminzadeh
Keyword(s):  
Elastic Properties ◽  
Fracture Zone ◽  
Seismic Data ◽  
Integrated Approach ◽  
Temporal Analysis ◽  
Microseismic Monitoring ◽  
Well Logs ◽  
Reservoir Properties ◽  
Velocity Models ◽  
Microseismic Data

We have characterized a promising geothermal prospect using an integrated approach involving microseismic monitoring data, well logs, and 3D surface seismic data. We have used seismic as well as microseismic data along with well logs to better predict the reservoir properties to try and analyze the reservoir for improved mapping of natural and induced fractures. We used microseismic-derived velocity models for geomechanical modeling and combined these geomechanical attributes with seismic and log-derived attributes for improved fracture characterization of an unconventional reservoir. We have developed a workflow to integrate these data to generate rock property estimates and identification of fracture zones within the reservoir. Specifically, we introduce a new “meta-attribute” that we call the hybrid-fracture zone-identifier attribute (FZI). The FZI makes use of elastic properties derived from microseismic as well as log-derived properties within an artificial neural network framework. Temporal analysis of microseismic data can help us understand the changes in the elastic properties with reservoir development. We demonstrate the value of using passive seismic data as a fracture zone identification tool despite issues with data quality.

Probabilistic petrophysical-properties estimation integrating statistical rock physics with seismic inversion

Geophysics ◽  
2010 ◽  
Vol 75 (3) ◽  
pp. O21-O37 ◽  
Author(s):  
Dario Grana ◽  
Ernesto Della Rossa
Keyword(s):  
Seismic Data ◽  
Measurement Errors ◽  
Rock Physics ◽  
Seismic Inversion ◽  
Joint Estimation ◽  
Physical Models ◽  
Inversion Method ◽  
Petrophysical Properties ◽  
Reservoir Properties ◽  
Statistical Rock Physics

A joint estimation of petrophysical properties is proposed that combines statistical rock physics and Bayesian seismic inversion. Because elastic attributes are correlated with petrophysical variables (effective porosity, clay content, and water saturation) and this physical link is associated with uncertainties, the petrophysical-properties estimation from seismic data can be seen as a Bayesian inversion problem. The purpose of this work was to develop a strategy for estimating the probability distributions of petrophysical parameters and litho-fluid classes from seismics. Estimation of reservoir properties and the associated uncertainty was performed in three steps: linearized seismic inversion to estimate the probabilities of elastic parameters, probabilistic upscaling to include the scale-changes effect, and petrophysical inversion to estimate the probabilities of petrophysical variables andlitho-fluid classes. Rock-physics equations provide the linkbetween reservoir properties and velocities, and linearized seismic modeling connects velocities and density to seismic amplitude. A full Bayesian approach was adopted to propagate uncertainty from seismics to petrophysics in an integrated framework that takes into account different sources of uncertainty: heterogeneity of the real data, approximation of physical models, measurement errors, and scale changes. The method has been tested, as a feasibility step, on real well data and synthetic seismic data to show reliable propagation of the uncertainty through the three different steps and to compare two statistical approaches: parametric and nonparametric. Application to a real reservoir study (including data from two wells and partially stacked seismic volumes) has provided as a main result the probability densities of petrophysical properties and litho-fluid classes. It demonstrated the applicability of the proposed inversion method.

Mature field Development to Periphery Area: Tambora West Flank development

2021 ◽  
Author(s):  
Y. S Priastomo
Keyword(s):  
Seismic Data ◽  
Sediment Provenance ◽  
Reservoir Properties ◽  
The West ◽  
Gas Field ◽  
Field Development ◽  
Dynamic Uncertainty ◽  
Mahakam Delta ◽  
Fully Connected ◽  
Positive Results

Tambora gas field, discovered in 1974 is located in a swamp area at the apex of Mahakam Delta, and it is adjacent to Nilam field, which is operated by another operator. Geologically, the Tambora and Nilam Fields have the same anticline structure that originates from the sediment provenance west of Kalimantan as reflected in present day Mahakam Delta. Therefore, this study aims to analyze the challenges to unlock the potential of the west flank area of Tambora Fields. The geological synthesis of both Tambora and Nilam fields shows similar net sand and pay distribution in lateral and vertical proportions. Most developments in the Tambora Anticline area are in the crest and the distances between wells are ~100-200m. Challenges to unlock potential in flank areas are derived from the limitation of wells and seismic data. Based on data and knowledge of the flank areas in both fields, the west flank has better productivity compared to the east. Therefore, geological synthesis is conducted in the west flank area to define hydrocarbon and reservoir properties. Furthermore, channel models were made from 2D seismic scouring, controlled by the continuation of well log channel facies in the anticline crest area. Based on the preliminary approach, 3 wells were proposed to unlock west flank Tambora potential and were integrated into the plan of development. Primarily, dynamic uncertainty affects the potential of the west flank since production in the anticline crest area is enormous, and the uncertainty was analyzed by drilling one recent well. The result shows that hydrocarbon in the flank is not fully connected with the anticline crest area and has proven the sidebar heterogeneity concept. These gave more confidence to seek further positive results and develop west flank Tambora to sustain Mahakam production in the future.

Quantitative 4D Seismic Assisted History Matching Using Ensemble-Based Methods on the Vilje Field

2020 ◽  
Author(s):  
Konrad Wojnar ◽  
Jon S?trom ◽  
Tore Felix Munck ◽  
Martha Stunell ◽  
Stig Sviland-Østre ◽  
...  
Keyword(s):  
Decision Making ◽  
Seismic Data ◽  
History Matching ◽  
Reservoir Characterization ◽  
Reservoir Management ◽  
History Match ◽  
Field Development ◽  
Qualitative And Quantitative ◽  
Reservoir Models ◽  
4D Seismic

Abstract The aim of the study was to create an ensemble of equiprobable models that could be used for improving the reservoir management of the Vilje field. Qualitative and quantitative workflows were developed to systematically and efficiently screen, analyze and history match an ensemble of reservoir simulation models to production and 4D seismic data. The goal of developing the workflows is to increase the utilization of data from 4D seismic surveys for reservoir characterization. The qualitative and quantitative workflows are presented, describing their benefits and challenges. The data conditioning produced a set of history matched reservoir models which could be used in the field development decision making process. The proposed workflows allowed for identification of outlying prior and posterior models based on key features where observed data was not covered by the synthetic 4D seismic realizations. As a result, suggestions for a more robust parameterization of the ensemble were made to improve data coverage. The existing history matching workflow efficiently integrated with the quantitative 4D seismic history matching workflow allowing for the conditioning of the reservoir models to production and 4D data. Thus, the predictability of the models was improved. This paper proposes a systematic and efficient workflow using ensemble-based methods to simultaneously screen, analyze and history match production and 4D seismic data. The proposed workflow improves the usability of 4D seismic data for reservoir characterization, and in turn, for the reservoir management and the decision-making processes.

scholarly journals Estimation of reservoir properties from seismic data by smooth neural networks

Geophysics ◽  
2003 ◽  
Vol 68 (6) ◽  
pp. 1969-1983 ◽  
Author(s):  
M. M. Saggaf ◽  
M. Nafi Toksöz ◽  
H. M. Mustafa
Keyword(s):  
Seismic Data ◽  
Reservoir Characterization ◽  
Back Propagation ◽  
Reservoir Rock ◽  
Seismic Survey ◽  
Rock Properties ◽  
Reservoir Properties ◽  
Network Parameters ◽  
Generalization Problem ◽  
Validation Tests

The performance of traditional back‐propagation networks for reservoir characterization in production settings has been inconsistent due to their nonmonotonous generalization, which necessitates extensive tweaking of their parameters in order to achieve satisfactory results and avoid overfitting the data. This makes the accuracy of these networks sensitive to the selection of the network parameters. We present an approach to estimate the reservoir rock properties from seismic data through the use of regularized back propagation networks that have inherent smoothness characteristics. This approach alleviates the nonmonotonous generalization problem associated with traditional networks and helps to avoid overfitting the data. We apply the approach to a 3D seismic survey in the Shedgum area of Ghawar field, Saudi Arabia, to estimate the reservoir porosity distribution of the Arab‐D zone, and we contrast the accuracy of our approach with that of traditional back‐propagation networks through cross‐validation tests. The results of these tests indicate that the accuracy of our approach remains consistent as the network parameters are varied, whereas that of the traditional network deteriorates as soon as deviations from the optimal parameters occur. The approach we present thus leads to more robust estimates of the reservoir properties and requires little or no tweaking of the network parameters to achieve optimal results.

scholarly journals Facies models of the Achimov Formation of East-Urengoiskoe license as the basis for optimizing exploration and field development patterns

Georesursy ◽  
2020 ◽  
Vol 22 (3) ◽  
pp. 55-61
Author(s):  
Alena V. Khramtsova ◽  
Sergey I. Pakhomov ◽  
Nikita Y. Natchuk ◽  
Мaria P. Kalashnikova ◽  
Sergey V. Romashkin ◽  
...  
Keyword(s):  
Seismic Data ◽  
Lower Cretaceous ◽  
Comprehensive Analysis ◽  
Core Analysis ◽  
Reservoir Properties ◽  
Development Patterns ◽  
Field Development ◽  
Submarine Fans ◽  
Well Correlation ◽  
Marine Basin

The results of sedimentological core analysis of the Achimov Formation (Upper Valanginian, Lower Cretaceous) confirm that it was formed by higher efficiency systems of submarine fans in (relatively) deep marine basin. Lithofacies models of Ach5-6 were generated, well correlation was performed based on the comprehensive analysis of core, well logging and seismic data. Distributary channels and proximal parts of depositional lobes are characterized by the best reservoir properties.

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