Application of Acoustic Impedance and Reflectivity in Reservoir Characterization

2021 ◽  
Author(s):  
Stanley Oifoghe ◽  
Ikenna Obodozie ◽  
Lucrecia Grigoletto

Abstract Well log analysis is one of the methods for reservoir characterization, in the oil and gas industry. Logs are used for subsurface formation evaluation. They are useful in hydrocarbon zone identification and volume calculation. Interpretation of well log involves sequential steps, which are lithology, shale volume, porosity and saturation determination. It is unwise to analyze well log without following the logical steps, as this could introduce errors in the result. Petrophysical and Geomechanical properties are two classes of properties for reservoir characterization. The computed volume of shale in the reservoir was 10%, the average water saturation was 30%, and the average porosity was 25pu. The bulk density decreased from 2.15g/cc to 1.95g/cc and there is a considerably lower acoustic impedance in the hydrocarbon bearing sands. In challenging reservoirs, where traditional petrophysical methods do not give definitive results, the use of geomechanical methods will improve interpretation certainty and help to clear doubts in the interpreted results.

2020 ◽  
Vol 21 (4) ◽  
pp. 41-48
Author(s):  
Layth Abdulmalik Jameel ◽  
Fadhil S. Kadhim ◽  
Hussein Al-Sudani

Petrophysical properties evaluation from well log analysis has always been crucial for the identification and assessment of hydrocarbon bearing zones. East Baghdad field is located 10 km east of Baghdad city, where the southern area includes the two southern portions of the field, Khasib formation is the main reservoir of East Baghdad oil field. In this paper, well log data of nine wells have been environmentally corrected, where the corrected data used to determine lithology, shale volume, porosity, and water saturation. Lithology identified by two methods; neutron-density and M-N matrix plots, while the shale volume estimated by single shale indicator and dual shale indicator, The porosity is calculated from the three common porosity logs; density log, neutron log, and sonic log, the water saturation is calculated by Indonesian model and Archie equation, and the results of the two methods were compared with the available core data to check the validity of the calculation. The results show that the main lithology in the reservoir is limestone, shale volume ranged between 0.152 to 0.249, porosity between 0.147 to 0.220, and water saturation from 0.627 to 0.966, the high-water saturation indicate that the water quantity is the determining factor of the reservoir units.


2018 ◽  
Author(s):  
Gulnaz Minigalieva ◽  
Albina Nigmatzyanova ◽  
Tatyana Burikova ◽  
Olga Privalova ◽  
Ruslan Akhmetzyanov ◽  
...  

2018 ◽  
Author(s):  
Gulnaz Minigalieva ◽  
Albina Nigmatzyanova ◽  
Tatyana Burikova ◽  
Olga Privalova ◽  
Ruslan Akhmetzyanov ◽  
...  

2021 ◽  
pp. 1-13
Author(s):  
Shantanu Chakraborty ◽  
Samit Mondal ◽  
Rima Chatterjee

Summary Fluid-replacement modeling (FRM) is a fundamental step in rock physics scenario modeling. The results help to conduct forward modeling for prediction of seismic signatures. Further, the analysis of the results improves the accuracy of quantitative interpretation and leads to an updated reservoir characterization. While modeling for different possible reservoir pore fluid scenarios, the quality of the results largely depends on the accuracy of the FRM. Gassmann (1951)fluid-replacement modeling (GFRM) is one of the widely adopted methods across the oil and gas industry. However, the Gassmann method assumes the reservoir as clean sandstone with connected pores. This causes Gassmann fluid-replacement results to overestimate the fluid effect in shaly sandstones. This study uses neutron and density logs to correct the overestimated results in shaly sandstone reservoirs. Due to the nature of these recordings, both of these log readings have close dependencies on the presence of shale. When the logs are plotted in a justified scale, the differences between the logs provide an accurate measurement of shaliness within the reservoir. The study has formulated a weight factor using the logs, which has further been used to scale the overestimated Gassmann-modeled fluid effect. The results of the revised method are independent of type of clay presence and associated effective porosity. Moreover, the corrected FRM results from the revised Gassmann method shows good agreement with rock physical interpretation of shaly sandstone reservoirs.


2020 ◽  
Vol 10 (8) ◽  
pp. 3263-3279 ◽  
Author(s):  
Mohamed Ragab Shalaby ◽  
Syamimi Hana Binti Sapri ◽  
Md Aminul Islam

Abstract An integrated reservoir characterization study is achieved on the Early to Middle Miocene Kaimiro Formation in the Taranaki Basin, New Zealand, to identify the quality of the formation as a potential reservoir. The Kaimiro Formation is a section of the Kapuni Group in the Taranaki Basin, consisting mainly of sandstone and a range of coastal plain through shallow marine facies. Several methods were accomplished for this study: petrophysical evaluation, sedimentological and petrographical descriptions and well log analysis. Based on the petrophysical study, the Kaimiro Formation is interpreted to have several flow units ranges up to 15 μm. Higher RQI and FZI reflect potential reservoir, while the pore size and pore throat diameters (r35) are found to be within the range of macro- and megapores, on the contrary to macropores related to poor reservoir quality concentrated in Tui-1 well. This is in good agreement with other measurements that show the formation is exhibited to be a good promising reservoir as the formation comprises a good average porosity of 19.6% and a good average permeability of 879.45 mD. The sedimentological and petrographical studies display that several diagenetic features have been affecting the formation such as compaction, cementation, dissolution and the presence of authigenic clay minerals. Although these features commonly occur, the impact on the reservoir properties and quality is minor as primary and secondary pores are still observed within the Kaimiro sandstone. Moreover, well log analysis is also completed to further ensure the hydrocarbon potential of the formation through a qualitative and quantitative analysis. It has been confirmed that the Kaimiro Formation is a promising reservoir containing several flow units with higher possibility for storage capacity.


2019 ◽  
Vol 10 (2) ◽  
pp. 537-555
Author(s):  
Aliyu Adebayo Sulaimon ◽  
Lim Lee Teng

Abstract Sand production is a major problem that the oil and gas industry has been facing for years. It can lead to loss of production, equipment damage or complete well abandonment. Prediction of sand has been historically challenging due to the periodic nature of sand production, insufficient laboratory tests and lack of field tests validation. Analyses have been performed to identify weak zones for planned wells, and common technique is the application of shear modulus and mechanical properties log (MPL) criteria developed by Tixier et al. (J Pet Technol 27:283–293, 1975). However, the set criteria have been found to be generally inadequate to detect transition zone or predict weak formation in some fields. In this study, using the knowledge of rock behavior, geomechanical properties and well log data, we have established new simple criteria for identifying fragile sections within a transition zone. In situ logging data from a field X, located in Sabah, Malaysia, and Field Y, located in Shimokita, Japan, were used in this study. Using the threshold for shear modulus and MPL, the criteria for the geomechanical properties are set to differentiate formation strengths at different depths. The threshold for Poisson’s ratio is 0.34, Young’s modulus at 1.6 × 106 psi and the unconfined compressive strength at 2400 psi. The MPL and geomechanical models were generated to predict sanding incident. The results were subsequently validated with artificial neural network using MATLAB. Also, critical wellbore pressure is calculated and acts as a guide to operate outside the sand failure envelope. Thus, the prediction of the weak formation using geomechanical properties has been further established in this study.


2020 ◽  
Vol 70 (1) ◽  
pp. 209-220
Author(s):  
Qazi Sohail Imran ◽  
◽  
Numair Ahmad Siddiqui ◽  
Abdul Halim Abdul Latif ◽  
Yasir Bashir ◽  
...  

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.


2021 ◽  
Vol 11 (2) ◽  
pp. 601-615
Author(s):  
Tokunbo Sanmi Fagbemigun ◽  
Michael Ayu Ayuk ◽  
Olufemi Enitan Oyanameh ◽  
Opeyemi Joshua Akinrinade ◽  
Joel Olayide Amosun ◽  
...  

AbstractOtan-Ile field, located in the transition zone Niger Delta, is characterized by complex structural deformation and faulting which lead to high uncertainties of reservoir properties. These high uncertainties greatly affect the exploration and development of the Otan-Ile field, and thus require proper characterization. Reservoir characterization requires integration of different data such as seismic and well log data, which are used to develop proper reservoir model. Therefore, the objective of this study is to characterize the reservoir sand bodies across the Otan-Ile field and to evaluate the petrophysical parameters using 3-dimension seismic and well log data from four wells. Reservoir sands were delineated using combination of resistivity and gamma ray logs. The estimation of reservoir properties, such as gross thickness, net thickness, volume of shale, porosity, water saturation and hydrocarbon saturation, were done using standard equations. Two horizons (T and U) as well as major and minor faults were mapped across the ‘Otan-Ile’ field. The results show that the average net thickness, volume of shale, porosity, hydrocarbon saturation and permeability across the field are 28.19 m, 15%, 37%, 71% and 26,740.24 md respectively. Two major faults (F1 and F5) dipping in northeastern and northwestern direction were identified. The horizons were characterized by structural closures which can accommodate hydrocarbon were identified. Amplitude maps superimposed on depth-structure map also validate the hydrocarbon potential of the closures on it. This study shows that the integration of 3D seismic and well log data with seismic attribute is a good tool for proper hydrocarbon reservoir characterization.


2016 ◽  
Vol 1 (1) ◽  
pp. 43 ◽  
Author(s):  
Sugeng Sapto Surjono ◽  
Indra Arifianto

Hydrocarbon potential within Upper Plover Formation in the Field “A” has not been produced due to unclear in understanding of reservoir problem. This formation consists of heterogeneous reservoir rock with their own physical characteristics. Reservoir characterization has been done by applying rock typing (RT) method utilizing wireline logs data to obtain reservoir properties including clay volume, porosity, water saturation, and permeability. Rock types are classified on the basis of porosity and permeability distribution from routines core analysis (RCAL) data. Meanwhile, conventional core data is utilized to depositional environment interpretations. This study also applied neural network methods to rock types analyze for intervals reservoir without core data. The Upper Plover Formation in the study area indicates potential reservoir distributes into 7 parasequences. Their were deposited during transgressive systems in coastal environments (foreshore - offshore) with coarsening upward pattern during Middle to Late Jurassic. The porosity of reservoir ranges from 1–19 % and permeability varies from 0.01 mD to 1300 mD. Based on the facies association and its physical properties from rock typing analysis, the reservoir within Upper Plover Formation can be grouped into 4 reservoir class: Class A (Excellent), Class B (Good), Class C (Poor), and Class D (Very Poor). For further analysis, only class A-C are considered as potential reservoir, and the remain is neglected.


1979 ◽  
Vol 19 (1) ◽  
pp. 197
Author(s):  
B.G. McKay ◽  
N.F. Taylor

The realistic estimation of reserves and resources is important to many diverse groups including explorers, producers, auditors, taxmen, bankers, shareholders and governments. Reserves data are used in different ways for a variety of reasons and often the figures are used without adequate definition and/or recognition of the uncertainties associated with them. Any calculation method which fails to consider the uncertainties involved, cannot portray a realistic assessment of reserves.Esso Australia Ltd. uses a relatively simple method to generate probability distribution curves in order to allow a more perceptive definition of the range of reserves for the offshore oil and gas fields in the Gippsland Basin and Esso is advocating wider petroleum and mineral industry acceptance of this approach.The method involves defining data distributions for each of the reservoir properties (volume, porosity, water saturation, compressibility and recovery factor) which are multiplied using Monte Carlo Simulation to generate the distribution of reserves. Actual input consists of data from:A high confidence area immediately surrounding well control, where the rock volume is relatively closely defined and the distributions of the other parameters, with the exception of recovery factors, reflect the observed variations.Other areas which are only seismically controlled, where the data ranges reflect both observed and interpreted variations in volume (gross and net), porosity, water saturation, compressibility and recovery factor.The curves generated for each area are then added by Monte Carlo Summation to yield the probability distribution of reserves for the whole field. In this method all available data are used and fewer subjective decisions are necessary. The computer generated distribution curves plot cumulative probability on the y-axis versus reserves on the x-axis. The curves allow the evaluation of the entire range of potential reserves, are valuable in economic and risk assessments and allow for more consistency in defining reserves for reporting purposes. The different categories of reserves, viz. "proved", "probable" or "possible", can be specified from the total field curves at defined probabilities. Moreover, the slope of the cumulative curve provides a direct indication of the level of knowledge of the field or parts of it.


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