scholarly journals APPLICATION OF SEISMIC METHODS FOR INTEGRATED RESERVOIR CHARACTERIZATION

Neft i gaz ◽  
2020 ◽  
Vol 3-4 (117-1118) ◽  
pp. 84-92
Author(s):  
A.K. ZHUMABEKOV ◽  
◽  
V.S. PORTNOV ◽  

3D seismic survey is the undisputed leader among tools of identifying potential exploration targets and reservoir characterization. This paper shows surveys that are crucial in the exploration and development of significant amounts of hydrocarbon resources, and can be used by operator companies to map complex geological structures and select better drilling locations. The purpose of research work is to have better understandings of formations and update previous studies in oil field of Mangyshlak Basin, Western Kazakhstan. The Main resultsare the acoustic impedance, Vp / Vs ratio, lithological and reservoir properties data. The quality *Автор для переписки. E-mail: [email protected] НЕФТЬ И ГАЗ 2020. 3–4 (117–118) 85 ГЕОФИЗИКА controls and analysis of results show good match with well logs and good recovery of seismic signal in inversion, but it should be improved in some areas. The results, from a scientific point of view, expand the already known geological and geophysical studies of the reservoir and improve the quality of interpretation using seismic methods in studying the sedimentation environment of the site.

2021 ◽  
Vol 266 ◽  
pp. 07009
Author(s):  
A.K. Zhumabekov ◽  
V.S. Portnov ◽  
L. Zhen

The 3D seismic survey is the undisputed leader among tools of identifying potential exploration targets and reservoir characterization. This paper shows surveys that are crucial in the exploration and development of significant amounts of hydrocarbon resources, and enables operator companies to map complex geological structures and select better drilling locations. The purpose of the research is to have better understandings of formations and update previous studies in the oil field of Mangyshlak Basin, Western Kazakhstan. The Main results are the acoustic impedance, Vp/Vs ratio, lithological and reservoir properties data. The quality controls and analysis of results show a good match with well logs and good recovery of seismic signal in inversion, but it should be improved in some areas. The results, from a scientific point of view, expand the already known geological and geophysical studies of the reservoir and improve the quality of interpretation using seismic methods in studying the sedimentation environment.


Geophysics ◽  
2001 ◽  
Vol 66 (5) ◽  
pp. 1450-1456 ◽  
Author(s):  
P. An ◽  
W. M. Moon ◽  
F. Kalantzis

Feedforward neural networks are used to estimate reservoir properties. The neural networks are trained with known reservoir properties from well log data and seismic waveforms at well locations. The trained neural networks are then applied to the whole seismic survey to generate a map of the predicted reservoir property. Both theoretical analysis and testing with synthetic models show that the neural networks are adaptive to coherent noise and that random noise in the training samples may increase the robustness of the trained neural networks. This approach was applied to a mature oil field to explore for Devonian reef‐edge oil by estimating the product of porosity and net pay thickness in northern Alberta, Canada. The resulting prediction map was used to select new well locations and design horizontal well trajectories. Four wells were drilled based on the prediction; all were successful. This increased production of the oil field by about 20%.


2018 ◽  
Vol 6 (3) ◽  
pp. SG33-SG39 ◽  
Author(s):  
Fabio Miotti ◽  
Andrea Zerilli ◽  
Paulo T. L. Menezes ◽  
João L. S. Crepaldi ◽  
Adriano R. Viana

Reservoir characterization objectives are to understand the reservoir rocks and fluids through accurate measurements to help asset teams develop optimal production decisions. Within this framework, we develop a new workflow to perform petrophysical joint inversion (PJI) of seismic and controlled-source electromagnetic (CSEM) data to resolve for reservoirs properties. Our workflow uses the complementary information contained in seismic, CSEM, and well-log data to improve the reservoir’s description drastically. The advent of CSEM, measuring resistivity, brought the possibility of integrating multiphysics data within the characterization workflow, and it has the potential to significantly enhance the accuracy at which reservoir properties and saturation, in particular, can be determined. We determine the power of PJI in the retrieval of reservoir parameters through a case study, based on a deepwater oil field offshore Brazil in the Sergipe-Alagoas Basin, to augment the certainty with which reservoir lithology and fluid properties are constrained.


Geophysics ◽  
2003 ◽  
Vol 68 (6) ◽  
pp. 1969-1983 ◽  
Author(s):  
M. M. Saggaf ◽  
M. Nafi Toksöz ◽  
H. M. Mustafa

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.


2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
P. A. Alao ◽  
S. O. Olabode ◽  
S. A. Opeloye

In the exploration and production business, by far the largest component of geophysical spending is driven by the need to characterize (potential) reservoirs. The simple reason is that better reservoir characterization means higher success rates and fewer wells for reservoir exploitation. In this research work, seismic and well log data were integrated in characterizing the reservoirs on “ALA” field in Niger Delta. Three-dimensional seismic data was used to identify the faults and map the horizons. Petrophysical parameters and time-depth structure maps were obtained. Seismic attributes was also employed in characterizing the reservoirs. Seven hydrocarbon-bearing reservoirs with thickness ranging from 9.9 to 71.6 m were delineated. Structural maps of horizons in six wells containing hydrocarbon-bearing zones with tops and bottoms at range of −2,453 to −3,950 m were generated; this portrayed the trapping mechanism to be mainly fault-assisted anticlinal closures. The identified prospective zones have good porosity, permeability, and hydrocarbon saturation. The environments of deposition were identified from log shapes which indicate a transitional-to-deltaic depositional environment. In this research work, new prospects have been recommended for drilling and further research work. Geochemical and biostratigraphic studies should be done to better characterize the reservoirs and reliably interpret the depositional environments.


2002 ◽  
Vol 5 (03) ◽  
pp. 190-196 ◽  
Author(s):  
R.L. Kaufman ◽  
H. Dashti ◽  
C.S. Kabir ◽  
J.M. Pederson ◽  
M.S. Moon ◽  
...  

Summary This study reports reservoir geochemistry findings on the Greater Burgan field by a multidisciplinary, multiorganizational team. The major objectives were to determine if unique oil fingerprints could be identified for the major producing reservoirs and if oil fingerprinting could be used to identify wells with mixed production because of wellbore mechanical problems. Three potential reservoir geochemistry applications in the Burgan field are:evaluation of vertical and lateral hydrocarbon continuity,identification of production problems caused by leaky tubing strings or leaks behind casing, andallocation of production to individual zones in commingled wells. Results from this study show that while oils from the major reservoir units are different from each other, the differences are small. Furthermore, a number of wells were identified in which mixed oils were produced because of previous mechanical problems. Both transient pressure testing and distributed pressure measurements provided corroborative evidence of some of these findings. Other data show that Third Burgan oils are different in the Burgan and Magwa sectors, suggesting a lack of communication across the central graben fault complex. This finding supports the geologic model for the ongoing reservoir simulation studies. Success of the geochemistry project has spawned enlargement of the study in both size and scope. Introduction This paper describes the results from a joint project by Chevron- Texaco Overseas Petroleum, the Kuwait Oil Co. (KOC), and the Kuwait Inst. for Scientific Research (KISR). Approximately 50 oils were analyzed to assess the feasibility of applying reservoir geochemistry in the Burgan field. All analytical work was performed at KISR. In this study, we report on a subset of these oils that contain primarily single-zone production samples. Reservoir geochemistry involves the study of reservoir fluids (oil, gas, and water) to determine reservoir properties and to understand the filling history of the field. Many established methods for exploration geochemistry can be used for this purpose. Reservoir geochemistry differs from other reservoir characterization methods by dealing primarily with the detailed molecular properties of the fluids in the C1-C35+ region rather than the physical properties. Larter and Aplin1 offer a review of many of these methods. Geochemistry techniques have been used to help solve reservoir problems for many years. During this time, oil geochemistry has been applied to the following reservoir characterization and management problems:Evaluation of hydrocarbon continuity.Analysis of commingled oils for production allocation.Identification of wellbore mechanical problems.Evaluation of workovers.Production monitoring for enhanced oil recovery (EOR).Identification of reservoir fluid type from rock extracts.Characterization of reservoir bitumens and tar mats. Many different analytical techniques have been used in these reservoir geochemistry studies. One of the most widely used is gas chromatography (GC). When used for oil correlation, it is often referred to as oil fingerprinting. In most reservoirs, the oil composition represents a unique fingerprint of the oil that can be used for correlation purposes.2 This is an inexpensive method and can be very cost-effective when compared to many production-logging methods. Of course, we recommend verifying this technique with other methods before reducing these more costly measurements. A number of papers have documented the application of oil fingerprinting to Middle East oil fields.3–7 Based on these studies, we felt that there was a high probability of success in using reservoir geochemistry in Kuwait's Burgan field. Three applications were of specific importance. Reservoir Continuity. The Burgan field contains several major producing horizons: the Wara, Third Burgan (Upper, Middle, and Lower), and Fourth Burgan reservoirs. Each of these is further subdivided into several reservoir layers. Vertical compartmentalization of the field, both in geologic and production time frames, is possible. In addition, a number of faults have been mapped in the field, and these may act as lateral barriers to fluid flow. The most significant faulting occurs in the central graben fault complex that separates the Burgan and Magwa/Ahmadi sectors of the field. Oil fingerprinting, along with other oilfield data, will be used to evaluate vertical and lateral compartmentalization in the field. Tubing-String Leaks. In many older fields, the integrity of casing strings and cement bonding is often a problem. If multiple pay zones are present, oil may leak into or behind the casing string from zones other than the completion interval. Many wells in the Burgan field produce from two reservoirs. Some wells, for example, produce Wara oil up the annulus and Third Burgan oil up the tubing string. When fingerprints of the individual oil zones have been identified, wellhead samples of the two production streams can be analyzed to determine if a mechanical problem is present.2,8 Production Allocation. It has been shown that the relative proportions of individual oils in an oil mixture can be determined with GC.9,10 Using this method to analyze production streams provides a rapid means of production allocation and does not require that wells be taken off production. In the Burgan field, this method will be applied to evaluate the extent of oil mixing either in the wellbore, owing to mechanical problems, or in the reservoir because of crossflow from deeper, higher-pressure reservoirs. The Burgan Oil Field The Greater Burgan oil field lies within the Arabian basin in the state of Kuwait. General reviews of the geology and producing history of the field are described by Brennan11 and by Kirby et al.12 The field is subdivided into the Burgan, Magwa, and Ahmadi sectors, based on the presence of three structural domes. Fig. 1 shows that the northern Magwa and Ahmadi sectors are separated from the southern Burgan sector by a central graben fault complex.


2018 ◽  
Vol 6 (2) ◽  
pp. SE23-SE37
Author(s):  
Laurie M. Weston Bellman

The objective of this case study is to predict geologic properties of a shale reservoir interval to guide production and completion planning for successful development of the reservoir. The conditioning, analysis, and blending of the converted-wave (PS) seismic data into a quantitative interpretation (QI) workflow are described in detail, illustrating the successful integration of geologic information and multiple seismic attributes. A multicomponent 3D seismic survey, several wells with dipole sonic logs, and a multicomponent (3C) 3D vertical seismic profile are available for the study. For comparisons of the incremental value of PS data, the QI workflow is completed entirely using only PP data and then modified and redone to incorporate information from the PS data. Predictions of the geologic properties for both workflows are assessed for accuracy against the existing well log and core evidence. Determining reservoir properties of the shale units of interest is important to the successful placement of horizontal wells for efficient multistage hydraulic fracturing and maximum gas production. Although conventional interpretation of conventional seismic data can only provide reservoir geometry, the quantitative analysis of prestack multicomponent data in this study reveals detailed distinctions between reservoir units and relative measures of porosity and brittleness bulk properties within each unit. Using all of the elastic properties derived from the seismic data analysis allowed for the classification of lithological units, which were, in turn, subclassified based on unit-specific reservoir properties. The upper reservoir units (Muskwa and Otter Park) were shown to have more variability in brittleness than the lower reservoir unit (Evie). Validation at a reliable well control confirmed these distinctive units and properties to be very high resolution and accurate, particularly when the PS data were incorporated into the workflow. The results of this method of analysis provided significantly more useful information for appraisal and development decisions than conventional seismic data interpretation alone.


Energies ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 5323
Author(s):  
Kamil Cichostępski ◽  
Jerzy Dec

In this article we present a novel method for the estimation of sulphur deposit resources based on high-resolution shallow reflection seismic survey and well logging. The study area was sited in the northern part of the Carpathian Foredeep (SE Poland), where sulphur ore occurs in carbonate rocks at a depth of about 120 m, with a thickness of approximately 25 m. The results of many years of seismic monitoring performed in the area of the sulphur deposit allowed us to determine the quantitative relationships between the amplitude of the seismic signal reflected from the top of the deposit and its petrophysical parameters such as porosity and sulphur content. The method of evaluating sulphur deposit is based on extensive statistics concerning the reservoir properties obtained from borehole data. We also discuss a methodology for conducting field acquisition and processing of seismic data in the aspect of mapping the actual amplitudes of the signal reflected from the top of a deposit. The results of estimating the abundance of carbonate sulphur deposits are presented based on the example of a seismic cross-section from the Osiek sulphur mine. Obtained results allow indicating the most prospective zones suitable for exploitation.


Geophysics ◽  
2011 ◽  
Vol 76 (2) ◽  
pp. W1-W13 ◽  
Author(s):  
Dengliang Gao

In exploration geology and geophysics, seismic texture is still a developing concept that has not been sufficiently known, although quite a number of different algorithms have been published in the literature. This paper provides a review of the seismic texture concepts and methodologies, focusing on latest developments in seismic amplitude texture analysis, with particular reference to the gray level co-occurrence matrix (GLCM) and the texture model regression (TMR) methods. The GLCM method evaluates spatial arrangements of amplitude samples within an analysis window using a matrix (a two-dimensional histogram) of amplitude co-occurrence. The matrix is then transformed into a suite of texture attributes, such as homogeneity, contrast, and randomness, which provide the basis for seismic facies classification. The TMR method uses a texture model as reference to discriminate among seismic features based on a linear, least-squares regression analysis between the model and the data within an analysis window. By implementing customized texture model schemes, the TMR algorithm has the flexibility to characterize subsurface geology for different purposes. A texture model with a constant phase is effective at enhancing the visibility of seismic structural fabrics, a texture model with a variable phase is helpful for visualizing seismic facies, and a texture model with variable amplitude, frequency, and size is instrumental in calibrating seismic to reservoir properties. Preliminary test case studies in the very recent past have indicated that the latest developments in seismic texture analysis have added to the existing amplitude interpretation theories and methodologies. These and future developments in seismic texture theory and methodologies will hopefully lead to a better understanding of the geologic implications of the seismic texture concept and to an improved geologic interpretation of reflection seismic amplitude.


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