Distinguishing gas-bearing sandstone reservoirs within mixed siliciclastic-carbonate sequences using extended elastic impedance: Nile Delta — Egypt

2016 ◽  
Vol 4 (4) ◽  
pp. T427-T441 ◽  
Author(s):  
Ahmed Hafez ◽  
John P. Castagna

In the Abu Madi Formation of the Nile Delta Basin, false bright spots may be misinterpreted as being indicative of hydrocarbons due to mixed clastics and carbonates. However, rock-physics analysis of well logs in a particular prospect area where such ambiguity exists suggests that attributes derived using extended elastic impedance (EEI) inversion may help identify hydrocarbons because they better show anomalous behavior in particular directions that are readily related to pore fluids and lithology. The EEI attributes calculated from well logs correlate extremely well to lithology and fluid properties, thereby differentiating amplitude anomalies caused by gas-bearing sandstones encased in shale from similar amplitudes caused by juxtaposition of high-impedance carbonates over lower impedance water-filled sandstones. Comparing seismically derived EEI attributes to well logs from a productive well and a nonproductive well indicates that seismic inversion can successfully identify lithologies such as shales, sandstones, carbonates, and anhydrite and distinguish gas-bearing from water-bearing sandstones. The technique can thus potentially be used to better delineate and risk prospects in the area, as well as assisting exploration efforts in other locations where similar ambiguities in amplitude interpretation exist.

2016 ◽  
Vol 56 (1) ◽  
pp. 341
Author(s):  
Jahan Zeb ◽  
Sanjeev Rajput ◽  
Jimmy Ting

Hydrocarbon reservoirs are characterised by integrating seismic, well-log and petrophysical information, which are dissimilar in spatial distribution, scale and relationship to reservoir properties. Well logs are essential for amplitude versus offset (AVO) modelling and seismic inversion. The usability of well logs can be determined during wavelet estimation, seismic-to-well ties, background model building, property distribution for inversion, deriving probability density functions and variograms, offset-to-angle conversion of seismic data, and many other processes. For the implementation of seismic inversion workflows, accurate and geologically corrected compressional-sonic, shear-sonic and density logs are necessary. Preparing the logs for quantitative interpretation becomes challenging in a real-field environment because of bad borehole conditions including washouts, uncalibrated and variability of logging tools, invasion effects, missing shear logs and change of borehole size. Conventional petrophysical analysis is usually restricted to the reservoir interval, the calculation of reservoir versus non-reservoir (including sands or shales), and log corrections for smaller intervals; in contrast, seismic petrophysics encompasses the entire geological interval, calculates the volume of multi-minerals, incorporates boundaries between non-reservoir and reservoir, and often includes the prediction of missing compressional and shear-sonic for AVO analysis. A detailed seismic petrophysics analysis was performed for amplitude versus angle (AVA) modelling and attributes analysis. To perform the AVA modelling, a series of forward models in association with rock physics modelled fluid-substituted logs were developed, and associated seismic responses for various pore fluids and rock types studied. The results reveal that synthetic seismic responses together with the AVA analysis show changes for various lithologies. AVA attributes analysis show trends in generated synthetic seismic responses for various fluid-substituted and porosity logs. Reservoir modelling and fluid substitution increases understanding of the observed seismic response. This paper describes detailed data analysis using various techniques to confirm the rock model for petrophysical evaluation, rock physics modelling, AVA analysis, pre-stack seismic inversion, and the scenario modelling applied to the study of an oil field in Australia.


2021 ◽  
Author(s):  
Pavlo Kuzmenko ◽  
Rustem Valiakhmetov ◽  
Francesco Gerecitano ◽  
Viktor Maliar ◽  
Grigori Kashuba ◽  
...  

Abstract The seismic data have historically been utilized to perform structural interpretation of the geological subsurface. Modern approaches of Quantitative Interpretation are intended to extract geologically valuable information from the seismic data. This work demonstrates how rock physics enables optimal prediction of reservoir properties from seismic derived attributes. Using a seismic-driven approach with incorporated prior geological knowledge into a probabilistic subsurface model allowed capturing uncertainty and quantifying the risk for targeting new wells in the unexplored areas. Elastic properties estimated from the acquired seismic data are influenced by the depositional environment, fluid content, and local geological trends. By applying the rock physics model, we were able to predict the elastic properties of a potential lithology away from the well control points in the subsurface whether or not it has been penetrated. Seismic amplitude variation with incident angle (AVO) and azimuth (AVAZ) jointly with rock-derived petrophysical interpretations were used for stochastical modeling to capture the reservoir distribution over the deep Visean formation. The seismic inversion was calibrated by available well log data and by traditional structural interpretation. Seismic elastic inversion results in a deep Lower Carboniferous target in the central part of the DDB are described. The fluid has minimal effect on the density and Vp. Well logs with cross-dipole acoustics are used together with wide-azimuth seismic data, processed with amplitude control. It is determined that seismic anisotropy increases in carbonate deposits. The result covers a set of lithoclasses and related probabilities: clay minerals, tight sandstones, porous sandstones, and carbonates. We analyzed the influence of maximum angles determination for elastic inversion that varied from 32.5 to 38.5 degrees. The greatest influence of the far angles selection is on the density. AI does not change significantly. Probably the 38,5 degrees provides a superior response above the carbonates. It does not seem to damage the overall AVA behavior, which result in a good density outcome, as higher angles of incidence are included. It gives a better tie to the wells for the high density layers over the interval of interest. Sand probability cube must always considered in the interpretation of the lithological classification that in many cases may be misleading (i.e. when sand and shale probabilities are very close to each other, because of small changes in elastic parameters). The authors provide an integrated holistic approach for quantitative interpretation, subsurface modeling, uncertainty evaluation, and characterization of reservoir distribution using pre-existing well logs and recently acquired seismic data. This paper underpins the previous efforts and encourages the work yet to be fulfilled on this subject. We will describe how quantitative interpretation was used for describing the reservoir, highlight values and uncertainties, and point a way forward for further improvement of the process for effective subsurface modeling.


2021 ◽  
Vol 40 (2) ◽  
pp. 151a1-151a7
Author(s):  
Adel Othman ◽  
Ahmed Ali ◽  
Mohamed Fathi ◽  
Farouk Metwally

In a complex reservoir with a significant degree of heterogeneity, it is a challenge to characterize the reservoir using different seismic attributes based on available data within certain time constraints. Prestack seismic inversion and amplitude variation with offset are among the techniques that give excellent results, particularly for gas-bearing clastic reservoir delineation because of the remarkable contrast between the latter and the surrounding rocks. Challenges arise when a shortage of seismic or well data presents an obstacle in applying these techniques. A further challenge arises if it is necessary to predict water saturation (Sw) using the seismic data because of the independent nonlinear relationship between Sw and seismic attributes and inversion products. Prediction of Sw is necessary not only for characterizing pay from nonpay reservoirs but also for economic reasons. Therefore, extended elastic impedance has been performed to produce a 3D volume of Sw over the reservoir interval. Then, a 3D sweetness volume and spectral decomposition volumes were used to grasp the geometry of the sand bodies that have been charged with gas in addition to their connectivity. This could help illustrate the different stages in the evolution of the Saffron channel system and the sand bodies distribution, both vertically and spatially, and consequently increase production and decrease development risk.


2015 ◽  
Vol 3 (4) ◽  
pp. SAE85-SAE93 ◽  
Author(s):  
Per Avseth ◽  
Tor Veggeland

We have developed a methodology to create easy-to-implement rock-physics attributes that can be used to screen for reservoir sandstones and hydrocarbon pore fill from seismic inversion data. Most seismic attributes are based on the empirical relationships between reservoir properties and seismic observables. We have honored the physical properties of the rocks by defining attributes that complied with calibrated rock-physics models. These attributes included the fluid saturation sensitive curved pseudo-elastic impedance (CPEI) and the rock stiffness/lithology attribute pseudo-elastic impedance for lithology (PEIL). We found that the CPEI attribute correlated nicely with saturation and resistivity, whereas the PEIL attribute in practice was a scaled version of the shear modulus and correlated nicely with porosity. We determined the use of these attributes on well log and seismic inversion data from the Norwegian Sea, and we successfully screened out reservoir rocks filled with either water or hydrocarbons.


2021 ◽  
Vol 11 (9) ◽  
pp. 3361-3371
Author(s):  
Amadou Hassane ◽  
Chukwuemeka Ngozi Ehirim ◽  
Tamunonengiyeofori Dagogo

AbstractEocene Sokor-1 reservoir is intrinsically heterogeneous and characterized by low-contrast low-resistivity log responses in parts of the Termit subbasin. Discriminating lithology and fluid properties using petrophysics alone is complicated and undermines reservoir characterization. Petrophysics and rock physics were integrated through rock physics diagnostics (RPDs) modeling for detailed description of the reservoir microstructure and quality in the subbasin. Petrophysical evaluation shows that Sokor-1 sand_5 interval has good petrophysical properties across wells and prolific in hydrocarbons. RPD analysis revealed that this sand interval could be best described by the constant cement sand model in wells_2, _3, _5 and _9 and friable sand model in well_4. The matrix structure varied mostly from clean and well-sorted unconsolidated sands as well as consolidated and cemented sandstones to deteriorating and poorly sorted shaly sands and shales/mudstones. The rock physics template built based on the constant cement sand model for representative well_2 diagnosed hydrocarbon bearing sands with low Vp/Vs and medium-to-high impedance signatures. Brine shaly sands and shales/mudstones were diagnosed with moderate Vp/Vs and medium-to-high impedance and high Vp/Vs and medium impedance, respectively. These results reveal that hydrocarbon sands and brine shaly sands cannot be distinctively discriminated by the impedance property, since they exhibit similar impedance characteristics. However, hydrocarbon sands, brine shaly sands and shales/mudstones were completely discriminated by characteristic Vp/Vs property. These results demonstrate the robust application of rock physics diagnostic modeling in quantitative reservoir characterization and may be quite useful in undrilled locations in the subbasin and fields with similar geologic settings.


2016 ◽  
Vol 4 (2) ◽  
pp. 76 ◽  
Author(s):  
Aniwetalu Emmanuel ◽  
Anakwuba Emmanuel ◽  
Ilechukwu Juliet N ◽  
Chidozie Okoye

The variations of pore pressure in Fabi Field Onshore Niger delta have been investigated using well log and seismic data. The both data were calibrated to ensure reasonable match in depth. Zones of overpressure were predicted from the well logs based on the deviations of petrophysical measurement from normal compaction trends. The lateral variations of the overpressure were delineated from seismic data through elastic impedance inversion. Overpressure cube was delineated from the inverted volumes through points of picked horizons. The results of the study revealed overpressure occurrence in well logs at depth level of 8625ft to 9000ft. The elastic impedance inversion presents overpressure variations beyond well control point at the depth level of about 1940-1140ms corresponding to very high impedance value of about 25540-27067ft/s*g/cc. The area extents of the positive anomalies (increase in elastic impedance) are mostly consistent with overpressure zones. Overpressure zones were also estimated from the seismic data between 1560ms -1600ms within the TRK-1 and TRK-2 horizon which also correspond to the well control points (8625ft to nearly 9000ft). The velocity and density crossplots revealed that undercompaction is the main overpressure generating mechanism in Fabi Field, although other parts of the field revealed unloading mechanism.


2021 ◽  
Author(s):  
Khalid Obaid ◽  
Muhammad Aamir ◽  
Tarek Yehia Nafie ◽  
Omar Aly ◽  
Widad Krissat ◽  
...  

Abstract Rock physics/seismic inversion is a powerful tool that deliver information about intra-wells rocks elastic attributes and reservoir properties such as porosity, saturation and rock lithology classification. In principle, inversion is like an engine that should be fueled by proper input quality of both seismic and well data. As for the well data, sonic and density logs measure the rock properties a few inches from the borehole. Reliability of sonic transit-time and bulk density logs can be affected by large and rapid variation in the diameter and shape of the borehole cross-section, as well as the process of drilling fluid invasion. The basic assumption for acoustic well logs editing and conditioning is to use other recorded logs (not affected by bad-hole conditions) in a Multivariate-Regression Algorithm. In addition, Fluid Substitution was implemented to correct for the mud invasion that affects the acoustic and elastic properties based on the PVT data for fluid properties computation. The logs were then quality checked by multiple cross-plotting comparisons to the standard Rock-physics trends templates. As for seismic data, there are several factors affecting the quality of surface seismic data including the presence of residual noise and multiples contamination that caused improper amplitude balancing. Optimizing the seismic data processing for the inversion studies require reviewing and conditioning the seismic gathers and pre-stack volumes, guided by a deterministic seismic-to-well tie analysis after every major stage of the processing sequence. The applied processes are mainly consisting of Curvelet domain noise attenuation to attenuate residual noise. This was followed by high resolution Radon anti-multiple to attenuate residual surface multiples and Extended interbed multiple prediction to attenuate interbed multiples. In addition, Offset dependent amplitude and spectral balancing were applied to maintain the seismic amplitudes fidelity. This paper will illustrate a case from Abu Dhabi where data conditioning results improved the Hydrocarbon saturated carbonates vs brine saturated carbonate and the lithology predictions, leading to optimizing field development plans and drilling operations.


2012 ◽  
Vol 4 (5) ◽  
pp. 05-20 ◽  
Author(s):  
Edward Moncayo ◽  
Nadejda Tchegliakova ◽  
Luis Montes

The Llanos basin is the most prolific of the Colombian basins; however few stratigraphic plays have been explored due to the uncertainty in determining the lithology of the channels. Inside a migrated 2D section, a wide channel was identified inside a prospective sandy unit of the Carbonera Formation, composed by intercalations of sand and shale levels, and considered a main reservoir in this part of the basin. However, the lithology filling the channel was unknown due to the absence of wells. To infer the channel lithology, and diminish the prospective risk a model based pre-stack seismic inversion was proposed.However, without well logs available along the line, the uncertain initial model diminishes reliance on the inversion. To circumvent this impasse, a seismic inversion with a genetic algorithm was proposed. The algorithm was tested on synthetic seismograms and real data from an area of the basin, where well logs were available. The error analysis between the expected and the inverted results, in both scenarios, pointed out a good algorithmic performance. Then, the algorithm was applied to the pre stack data of the 2D line where the channel had been identified.According to the inverted results and rock physics analysis of wells near the seismic line with comparative geology, classified the channel was described as to be filled by silt, shale and probably some levels of shaly sands, increasing the exploratory risk because this lithology has low porosity and permeability, contrary to the producing reservoirs in neighbor fields, characterized by clean sands of high porosity. The algorithm is useful in areas with few or no borehole logs.


Sign in / Sign up

Export Citation Format

Share Document