Pub Date : 2018-06-11DOI: 10.3997/2214-4609.201801603
T. Zhang, D. Wei, R. Xiong, D. Li, Y. Wang
Carbonate rocks dissolution kinetics, under burial condition, is crucial to carbonate petroleum reservoirs exploration. The experiment investigates dolomitic limestone dissolution kinetics in acetic acid solution with pH 4.4 at temperatures of 75℃ to 200℃, P=30MPa using the continuous flow column pressure vessel reactor, to model the dolomitized limestone dissolve under burial condition. The result indicates the component of MgCO3 is more sensitive than CaCO3 as environment change. The rates increase with as the temperature goes up and the flow velocity speeds up. From the lowest, 7.981×10-12 mol • cm-2 • s-1, at 75℃, to the highest 7.310×10-11 mol • cm-2 • s-1, the dissolution rates rise by a factor of ten. The dissolution mechanisms above 175℃ are extremely different from the below. Moreover, the distance from equilibrium could influence on the mechanism. The switch concentrations Cs vary with temperature yet. The activity energy Ea is 15.195 kJ• mol-1, showing the diffusion control at T=75～125℃; The reaction lacks sufficient data at T=150~200℃, needing further research.
{"title":"The Experiment of Burial Dissolution Kinetics for Dolomitized Limestone","authors":"T. Zhang, D. Wei, R. Xiong, D. Li, Y. Wang","doi":"10.3997/2214-4609.201801603","DOIUrl":"https://doi.org/10.3997/2214-4609.201801603","url":null,"abstract":"Carbonate rocks dissolution kinetics, under burial condition, is crucial to carbonate petroleum reservoirs exploration. The experiment investigates dolomitic limestone dissolution kinetics in acetic acid solution with pH 4.4 at temperatures of 75℃ to 200℃, P=30MPa using the continuous flow column pressure vessel reactor, to model the dolomitized limestone dissolve under burial condition. The result indicates the component of MgCO3 is more sensitive than CaCO3 as environment change. The rates increase with as the temperature goes up and the flow velocity speeds up. From the lowest, 7.981×10-12 mol • cm-2 • s-1, at 75℃, to the highest 7.310×10-11 mol • cm-2 • s-1, the dissolution rates rise by a factor of ten. The dissolution mechanisms above 175℃ are extremely different from the below. Moreover, the distance from equilibrium could influence on the mechanism. The switch concentrations Cs vary with temperature yet. The activity energy Ea is 15.195 kJ• mol-1, showing the diffusion control at T=75～125℃; The reaction lacks sufficient data at T=150~200℃, needing further research.","PeriodicalId":325587,"journal":{"name":"80th EAGE Conference and Exhibition 2018","volume":"141 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115139859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-11DOI: 10.3997/2214-4609.201801672
D. Dziubacki
Summary Thin-skinned tectonics is related to the shallow crust imbrication structures separated from the basement by basal sole thrust or decollement. Their origin is mainly connected with contractional regimes. Such deformation are common in the foreland of orogenic belts, contractional parts of delta deposits or areas influenced by basin inversion. As an example late-Carboniferous thin-skinned structures from Lublin Basin, Poland were considered. Due to complex geological background exact origin and architecture of tectonic structure is still the subject of research. Interpretation of the structures was conducted on the basis of several 2D seismic lines. For faults and folds identification improvement several seismic attributes were calculated: Similarity, Cosine Phase, Instantaneous Frequency. As a result they give information about lateral continuity of reflections and coherence. Clear changes on the sections of these parameters indicate places where faults exist. Geophysical data were supplied by geological information (e.g. core analysis data). Thanks to the well-tie a few horizons were picked. Discontinuity of horizons was also clear evidence of fault existence. Combination of seismic data with its attributes and geological information leads to more accurate interpretation.
{"title":"Interpretation of Late Carboniferous Thin-Skinned Structures on a Seismic Image","authors":"D. Dziubacki","doi":"10.3997/2214-4609.201801672","DOIUrl":"https://doi.org/10.3997/2214-4609.201801672","url":null,"abstract":"Summary Thin-skinned tectonics is related to the shallow crust imbrication structures separated from the basement by basal sole thrust or decollement. Their origin is mainly connected with contractional regimes. Such deformation are common in the foreland of orogenic belts, contractional parts of delta deposits or areas influenced by basin inversion. As an example late-Carboniferous thin-skinned structures from Lublin Basin, Poland were considered. Due to complex geological background exact origin and architecture of tectonic structure is still the subject of research. Interpretation of the structures was conducted on the basis of several 2D seismic lines. For faults and folds identification improvement several seismic attributes were calculated: Similarity, Cosine Phase, Instantaneous Frequency. As a result they give information about lateral continuity of reflections and coherence. Clear changes on the sections of these parameters indicate places where faults exist. Geophysical data were supplied by geological information (e.g. core analysis data). Thanks to the well-tie a few horizons were picked. Discontinuity of horizons was also clear evidence of fault existence. Combination of seismic data with its attributes and geological information leads to more accurate interpretation.","PeriodicalId":325587,"journal":{"name":"80th EAGE Conference and Exhibition 2018","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115150099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-11DOI: 10.3997/2214-4609.201800954
R. Akinwale, O. Akinwale, O. Waliu
{"title":"Enhancing Subsurface Disposition Using Visual Rendering of 3D Iso -Resistivity Surfaces","authors":"R. Akinwale, O. Akinwale, O. Waliu","doi":"10.3997/2214-4609.201800954","DOIUrl":"https://doi.org/10.3997/2214-4609.201800954","url":null,"abstract":"","PeriodicalId":325587,"journal":{"name":"80th EAGE Conference and Exhibition 2018","volume":"159 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115403430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-11DOI: 10.3997/2214-4609.201801739
T. Rajkumar
Summary This paper addresses the approach to invert parameters of different buried structures using their self-potential (SP) anomalies. This approach involves a Laplace Crossover (LX) operator based Genetic Algorithm (GA) to invert synthetic SP anomaly of buried sphere, cylinder and inclined sheet. GA is used to determine depth, shape factor, polarization angle, origin of anomaly, electric current dipole for sphere and cylinder and half width along with the mentioned parameters for inclined sheet. This study of the synthetic examples shows that the proposed GA works very well with both noise free and noise corrupted data. Since it gives good convergence of the inverted data to the original values of synthetic examples, it can also be used in interpretation of real field complex SP data.
{"title":"Inversion of Self-Potential Anomaly Using Laplace Crossover Operator Based Genetic Algorithm","authors":"T. Rajkumar","doi":"10.3997/2214-4609.201801739","DOIUrl":"https://doi.org/10.3997/2214-4609.201801739","url":null,"abstract":"Summary This paper addresses the approach to invert parameters of different buried structures using their self-potential (SP) anomalies. This approach involves a Laplace Crossover (LX) operator based Genetic Algorithm (GA) to invert synthetic SP anomaly of buried sphere, cylinder and inclined sheet. GA is used to determine depth, shape factor, polarization angle, origin of anomaly, electric current dipole for sphere and cylinder and half width along with the mentioned parameters for inclined sheet. This study of the synthetic examples shows that the proposed GA works very well with both noise free and noise corrupted data. Since it gives good convergence of the inverted data to the original values of synthetic examples, it can also be used in interpretation of real field complex SP data.","PeriodicalId":325587,"journal":{"name":"80th EAGE Conference and Exhibition 2018","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124434896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-11DOI: 10.3997/2214-4609.201800811
C. Feng, X. Deng, Z. Wang, T. Sun, Y. Hu
{"title":"An Empirical Relation between Static and Dynamic Brittleness Indices","authors":"C. Feng, X. Deng, Z. Wang, T. Sun, Y. Hu","doi":"10.3997/2214-4609.201800811","DOIUrl":"https://doi.org/10.3997/2214-4609.201800811","url":null,"abstract":"","PeriodicalId":325587,"journal":{"name":"80th EAGE Conference and Exhibition 2018","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124439821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-11DOI: 10.3997/2214-4609.201800872
Y. Ye, Q. Guo, X. Zhuang, L. Li, B. Wang, Z. Q. Wang
{"title":"One-way Wave-equation Migration of Different Order Surface-related Multiples: An Application to Deep Marine Data","authors":"Y. Ye, Q. Guo, X. Zhuang, L. Li, B. Wang, Z. Q. Wang","doi":"10.3997/2214-4609.201800872","DOIUrl":"https://doi.org/10.3997/2214-4609.201800872","url":null,"abstract":"","PeriodicalId":325587,"journal":{"name":"80th EAGE Conference and Exhibition 2018","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124457239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-11DOI: 10.3997/2214-4609.201801295
M. Farahani, R. Shams, S. Jamshidi
{"title":"A Robust Modeling Approach for Predicting the Rheological Behavior of Thixotropic Fluids","authors":"M. Farahani, R. Shams, S. Jamshidi","doi":"10.3997/2214-4609.201801295","DOIUrl":"https://doi.org/10.3997/2214-4609.201801295","url":null,"abstract":"","PeriodicalId":325587,"journal":{"name":"80th EAGE Conference and Exhibition 2018","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121822858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-11DOI: 10.3997/2214-4609.201800920
I. Priezzhev, E. Stanislav
This paper provides for a comparison of the classic seismic inversion technique with several multivariate predictive techniques based on machine learning algorithms (linear regression, ACE regression, Random Forest, Neural Network) using seismic data and well logs to estimate rock physical properties. Currently, the estimation of reservoir properties is commonly based on comparative analysis of the distribution of the properties in wells and the elastic properties according to the results of the seismic inversion. Most of the commercial seismic inversion technologies are based on the classical one-dimensional models of seismic exploration involving plane-parallel medium that is described by the linear convolution equation. However, presumably, in some complex cases the linear operators of convolution type cannot properly describe the seismic field distribution. It is assumed that there is a nonlinear absorption of energy of seismic waves in some geological environments, such as in fractured, fluid - rich layers. Such nonlinearity can be shown by vertical and horizontal changes in the seismic wavelet. This paper aims to demonstrate that in certain nonlinear cases using a nonlinear predictive operator based on machine learning algorithms allows to estimate rock physical properties more accurately.
{"title":"Application of Machine Learning Algorithms Using Seismic Data and Well Logs to Predict Reservoir Properties","authors":"I. Priezzhev, E. Stanislav","doi":"10.3997/2214-4609.201800920","DOIUrl":"https://doi.org/10.3997/2214-4609.201800920","url":null,"abstract":"This paper provides for a comparison of the classic seismic inversion technique with several multivariate predictive techniques based on machine learning algorithms (linear regression, ACE regression, Random Forest, Neural Network) using seismic data and well logs to estimate rock physical properties. Currently, the estimation of reservoir properties is commonly based on comparative analysis of the distribution of the properties in wells and the elastic properties according to the results of the seismic inversion. Most of the commercial seismic inversion technologies are based on the classical one-dimensional models of seismic exploration involving plane-parallel medium that is described by the linear convolution equation. However, presumably, in some complex cases the linear operators of convolution type cannot properly describe the seismic field distribution. It is assumed that there is a nonlinear absorption of energy of seismic waves in some geological environments, such as in fractured, fluid - rich layers. Such nonlinearity can be shown by vertical and horizontal changes in the seismic wavelet. This paper aims to demonstrate that in certain nonlinear cases using a nonlinear predictive operator based on machine learning algorithms allows to estimate rock physical properties more accurately.","PeriodicalId":325587,"journal":{"name":"80th EAGE Conference and Exhibition 2018","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121832698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-11DOI: 10.3997/2214-4609.201801443
E. Raknes, A. Osen, R. Pettersen, E. Rykkelid, Ø. Runde
Summary The Frigg Gamma and Frigg Delta are oil and gas discoveries offshore Norway with a reservoir in the Frigg Formation at approximately 2000 m depth. The overburden is characterized by a set of complex effects that result in strong deterioration of the seismic image over the Frigg Gamma structure, whereas the Frigg Delta structure is relatively well resolved. Several seismic acquisition and processing projects have attempted to improve the seismic imaging in the area, but so far not adequately resolved these problems. In this study, we describe the structural setting causes the seismic imaging challenges. We construct a set of synthetic velocity models from well data, and study the effects of seismic imaging algorithms and their sensitivity to the velocity models. We show a model with vertical chimney-like cemented zones which creates pull up in time and strong scattering that resemble the real data.
{"title":"Understanding the imaging challenges at the Frigg Gamma discovery","authors":"E. Raknes, A. Osen, R. Pettersen, E. Rykkelid, Ø. Runde","doi":"10.3997/2214-4609.201801443","DOIUrl":"https://doi.org/10.3997/2214-4609.201801443","url":null,"abstract":"Summary The Frigg Gamma and Frigg Delta are oil and gas discoveries offshore Norway with a reservoir in the Frigg Formation at approximately 2000 m depth. The overburden is characterized by a set of complex effects that result in strong deterioration of the seismic image over the Frigg Gamma structure, whereas the Frigg Delta structure is relatively well resolved. Several seismic acquisition and processing projects have attempted to improve the seismic imaging in the area, but so far not adequately resolved these problems. In this study, we describe the structural setting causes the seismic imaging challenges. We construct a set of synthetic velocity models from well data, and study the effects of seismic imaging algorithms and their sensitivity to the velocity models. We show a model with vertical chimney-like cemented zones which creates pull up in time and strong scattering that resemble the real data.","PeriodicalId":325587,"journal":{"name":"80th EAGE Conference and Exhibition 2018","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116641388","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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