Post-stack Seismic Attributes Research Articles

Adaptive fault enhancement in OVT domain based on anisotropy theory

As a result of the combined influence of multi-stage and multi-directional tectonic activities, the subsurface medium in complex structural areas can easily develop intricate fault systems with varying scales and directions. Post-stack seismic and azimuth-stack attributes have limited precision in recognizing such complex fault systems. In this paper, we propose an adaptive fault enhancement workflow in offset vector tile (OVT) domain based on anisotropy theory to improve the recognition ability of seismic data for multi-directional faults and minor faults. The vertical directions of fault strikes and tectonic strikes estimated by the gradient structure tensor (GST) can be used as sensitive observation azimuths of faults. At the same time, according to the anisotropic forward modeling and real data amplitude variation with offset (AVO) analysis of minor faults in marine shale of Wufeng-Longmaxi formations in Sichuan Basin, China, the incident angles with the largest difference between isotropic and anisotropic reflection coefficients can be used as sensitive incident angles of faults. A new fault enhancement seismic data can be reconstructed from the OVT gathers by traversing the sensitive azimuths and incident angles adaptively. The 3D model and real data indicate that the faults enhanced by the workflow we proposed are clearer in shape, smaller in scale, and richer in details, which is consistent with geology and well.

Structural and seismic attribute analysis of the Paleocene carbonate reservoir from the Balkassar Field, Potwar Plateau, Pakistan

The structural and seismic properties of the Paleocene carbonate reservoir are re-evaluated, using 3D seismic data multi-attributes, to improve reservoir prediction accuracy rarely documented earlier. This study highlights a number of relevant post-stack seismic attributes for understanding the structural setup and seismic properties of a carbonate reservoir. The structural analysis was carried out using seismic interpretation, combined with multi-attribute analysis for prospect actualization and generation of a 3D structural model to determine the structural aspect. The structural interpretation reveals the presence of faults and an asymmetrical anticlinal structure demonstrating a four-way closure, confirming compressional tectonics. The high amplitude anomaly (-6 to 12) combined with the RMS attribute (23 to 32) suggests bright spots in the Paleocene carbonate reservoir and gas saturated zone, the variance attribute (0.05 to 0.03) highlights the presence of two major faults, and the lower instantaneous frequency demonstrates the presence of hydrocarbons. The attribute results indicate that the Lockhart Limestone possesses good reservoir potential as revealed by DHI (bright spot), gas saturated zone and a trapping mechanism supported by four-way structure closure in the region and can help to understand analogous carbonate reservoirs in similar geological settings around the world.

A preliminary analysis of natural CO2-saturated gas sands distribution in the Gemah Field-Jabung Block, South Sumatra Basin, Indonesia, by using simple seismic attributes

The discovery of CO2-saturated gas in sandstone reservoirs of the Lower Talang Akar Formation (LTAF) in the Jabung Block of South Sumatra Basin is a significant exploration risk that affects development plans. Gemah Field is one of the fields that produces CO2-saturated gas in the area. The field has several oil rims that can be optimized for production by using carbon capture, utilization, and storage (CCUS) enhanced oil recovery (EOR). This paper discusses a preliminary analysis of the natural CO2-saturated gas sands distribution in the FS3 interval of Gemah Field by using simple seismic attributes. The results can be used for guiding the feasibility analysis of CCUS-EOR implementation and mitigation of drilling risk of subsequent developments wells. Poststack seismic attributes and inversion analysis were performed and constrained by data from 64 wells in the FS3 interval. Although these two methods give similar distribution of sandstone reservoirs, this study finds that the sum of negative amplitude (SNA) attribute is better because there is a linear relationship between SNA with sand thickness and CO2 saturation. High CO2 saturation gas reservoir zones are observed along the highly faulted areas. CO2 saturation decreases away from the faulted areas and follows the northeast–southwest direction of reservoir deposition. The identified high CO2 regions can be considered as zones of potential CO2 sources for CCUS-EOR. The low CO2 areas are a potential location for a subsequent drilling well to obtain cleaner gas reservoirs with low CO2 saturation.

Supervised machine learning for discriminating fluid saturation and presence in subsurface reservoirs

This paper describes a workflow that combines machine learning and frequency-related multi-attribute analyses to predict the occurrence of water, oil, and high or low gas saturations in three Miocene Gulf of Mexico clastic reservoirs, the Ursa, King Kong and Lisa Anne fields. The models are trained on labeled data from the Ursa Field dataset and validation is conducted on the King Kong and Lisa Anne Field datasets, comprising four wells with oil and varying gas saturations. We also analyze the impact of fluid-type and saturation on a suite of frequency-related attributes, including independent frequency magnitudes and spectral shape attributes.We also assess feature significance using SHAP Analysis and our results indicate that that high gas saturation is characterized by high magnitudes of low frequencies, increased bandwidth, and lower skewness and kurtosis values. Conversely, low gas saturation is distinguished by high magnitudes of medium frequencies, reduced bandwidth, and higher skewness and kurtosis values.Our workflow demonstrates the power and utility of supervised machine learning for reservoir fluid identification and saturation prediction. Human interpreters relying solely on post-stack seismic data may find the task of reservoir fluid predictions challenging and the results may be compromised by subjectivity. This study underscores the potential of machine learning to improve hydrocarbon exploration and production, providing a more robust approach to prospect risk assessment using post-stack seismic data and frequency attributes.

Geophysical prediction of organic matter abundance in source rocks based on geochemical analysis: A case study of southwestern Bozhong Sag, Bohai Sea, China

The Bozhong Sag is the largest petroliferous sag in the Bohai Bay Basin, and the source rocks of Paleogene Dongying and Shahejie Formations were buried deeply. Most of the drillings were located at the structural high, and there were few wells that met good quality source rocks, so it is difficult to evaluate the source rocks in the study area precisely by geochemical analysis only. Based on the Rock-Eval pyrolysis, total organic carbon (TOC) testing, the organic matter (OM) abundance of Paleogene source rocks in the southwestern Bozhong Sag were evaluated, including the lower of second member of Dongying Formation (E3d2L), the third member of Dongying Formation (E3d3), the first and second members of Shahejie Formation (E2s1+2), the third member of Shahejie Formation (E2s3). The results indicate that the E2s1+2 and E2s3 have better hydrocarbon generative potentials with the highest OM abundance, the E3d3 are of the second good quality, and the E3d2L have poor to fair hydrocarbon generative potential. Furthermore, the well logs were applied to predict TOC and residual hydrocarbon generation potential (S2) based on the sedimentary facies classification, using ΔlogR, generalized ΔlogR, logging multiple linear regression and BP neural network methods. The various methods were compared, and the BP neural network method have relatively better prediction accuracy. Based on the pre-stack simultaneous inversion (P-wave impedance, P-wave velocity and density inversion results) and the post-stack seismic attributes, the three-dimensional (3D) seismic prediction of TOC and S2 was carried out. The results show that the seismic near well prediction results of TOC and S2 based on seismic multi-attributes analysis correspond well with the results of well logging methods, and the plane prediction results are identical with the sedimentary facies map in the study area. The TOC and S2 values of E2s1+2 and E2s3 are higher than those in E3d3 and E3d2L, basically consistent with the geochemical analysis results. This method makes up the deficiency of geochemical methods, establishing the connection between geophysical information and geochemical data, and it is helpful to the 3D quantitative prediction and the evaluation of high-quality source rocks in the areas where the drillings are limited.

Fluid Accumulation Zone by Seismic Attributes and Amplitude Versus Offset Analysis at Solfatara Volcano, Campi Flegrei, Italy

The imaging of volcanic systems is a challenging topic that attracts the scientific community’s attention. The characterization of structures and rock properties by means of seismic active methods is becoming fundamental for providing ultra-high-resolution images of the structures of interest. The Solfatara Volcano is a quiescent volcano in the Campi Flegrei resurgent nested caldera that is continuously under investigation and monitoring for its shallow activity, such as fumaroles. The purpose of this work is to characterize the fluid accumulation zone in the first 150 m depth in the middle of the crater, using several post-stack seismic attributes and Amplitude Versus Offset (AVO) analysis to characterize the contact between the CO2 and condensed water in the shallower accumulation zone. The two 400 m-long profiles to which we refer in this work have been acquired during the active Repeated InduCed Earthquakes and Noise experiment. The profiles were deployed along with the NNE-SSW and WNW-ESE directions across the whole surface of the crater including the main surface anomalies of the fumaroles, in the eastern area, and the mud-pool of Fangaia, located in the western area. The seismic pre-processing, pre-stack processing, and post-stack analysis previously applied on the NNE-SSW profile are here performed for the first time on the WNW-ESE profile, while partial-stack AVO analysis is performed for both profiles. The post-stack attributes including time gain, envelope, energy, and root mean square have been computed and extracted for determining the maximum and minimum values of amplitude zones on the migrated post-stack seismic profiles. Such anomalies are provided by complex and geometrical attributes embedding information on faults and chaotic zones. The AVO technique has also been used as a direct gas indicator to enhance fluid discrimination and identification. Finally, the analysis of the profile, seismic attributes, and near-surface structural interpretation related to the Solfatara Volcano has been incorporated into the proposed analysis. The multi-2D image depicts fluids trapped in the Solfatara Volcano at depths ranging from 10 to 50 m below the crater’s surface, as well as their migration paths up to 150 m deep: this evidenced contact between the fluids has been probably due to the solfataric alteration of the minerals, caused by the arising plume and the abovecondensed water which decreases the permeability of the rocks and forms an argillic phase working as cap-rock and trapping the gases. The application of the AVO analysis, coupled with the seismic attribute’s investigation, provides a very detailed multi-2D image of the shallower Solfatara Volcano, which outperforms in terms of accuracy the ones obtained with different tools in previous works, and that evidences the presence and the position of the liquid and the gases in the north-east area of the Solfatara Volcano.

Influence of Depositional and Diagenetic Processes on Caprock Properties of CO2 Storage Sites in the Northern North Sea, Offshore Norway

Characterization of caprock shale is critical in CO2 storage site evaluation because the caprock shale acts as a barrier for the injected buoyant CO2 plume. The properties of shales are complex and influenced by various processes; hence, it is challenging to evaluate the caprock quality. An integrated approach is therefore necessary for assessing seal integrity. In this study, we investigated the caprock properties of the Lower Jurassic Drake Formation shales from the proposed CO2 storage site Aurora (the Longship/Northern Lights CCS project), located in the Horda Platform area, offshore Norway. Wireline logs from 50 exploration wells, various 2D seismic lines, and two 3D seismic cubes were used to investigate the variations of the caprock properties. The Drake Formation was subdivided into upper and lower Drake units based on the lithological variations observed. Exhumation and thermal gradient influencing the caprock properties were also analyzed. Moreover, rock physics diagnostics were carried out, and caprock property maps were generated using the average log values to characterize the Drake Formation shales. In addiiton, pre-stack seismic-inverted properties and post-stack seismic attributes were assessed and compared to the wireline log-based analysis. The sediment source controlled at 61° N significantly influenced the depositional environment of the studied area, which later influenced the diagenetic processes and had various caprock properties. The upper and lower Drake units represent similar geomechanical properties in the Aurora area, irrespective of significant lithological variations. The Drake Formation caprock shale near the injection site shows less-ductile to less-brittle brittleness values. Based on the caprock thickness and shaliness in the Aurora injection site, Drake Formation shale might act as an effective top seal. However, the effect of injection-induced pressure changes on caprock integrity needs to be evaluated.

Selection of Sensitive Post-Stack and Pre-Stack Seismic Inversion Attributes for Improved Characterization of Thin Gas-Bearing Sands

Selection of Sensitive Post-Stack and Pre-Stack Seismic Inversion Attributes for Improved Characterization of Thin Gas-Bearing Sands

Seismic impedance inversion and attribute analysis for reservoir characterization in an offshore depobelt, Niger Delta, Nigeria

The task of minimizing pitfall in quantitative reservoir assessment and evaluation is an integral aspect of any promising petroleum exploration and evaluation project. The Niger Delta oil province in Nigeria is chiefly composed of several pay zones with many stratigraphic intervals of sand and shale formations in varying proportion. Whereas conventional seismic interpretation technique poses certain degree of uncertainty in reservoir characterization, seismic inversion constraint by log data brings significant improvement in interpretation that reduces uncertainty in the delineation of reservoir characteristics, volume and distribution. In this present study, post-stack seismic inversion and seismic attributes analysis were used to evaluate the potentials and prospects of mapped reservoirs in a field, offshore depobelt, Niger Delta. The implementation of the tasks consists of mapping of structural framework, horizon picking, log editing and correlation, wavelet extraction, building of low-frequency model, acoustic impedance inversion and crossplot analysis of reservoir properties and attributes. A hybrid approach (formulated using Greenberg-Castagna equation) specific for the Niger Delta depobelts was used to estimate and generate shear wave velocity for the wells. Results obtained from inversion depict an acoustic impedance values in the range 150–280 ft/s g/cc and $$V_{\text{P}}/V_{\text{S}}$$ of 1.25–2.50 at a depth range of 9250–9280 ft within the hydrocarbon-bearing sands in the two wells. Region of low acoustic impedance (representing high reservoir porosity) coupled with a corresponding low $$V_{\text{P}}/V_{\text{S}}$$ ratio (indicating hydrocarbon accumulation) is presumed to have high prospects for exploration and well development. Altogether the degree of correlation between the inverted and actual impedance was found to be about 90% across the wells. It is evident that the acoustic impedance slice at 3000 ms depicts low acoustic impedance sand within 18,500–20,000 ft/s g/cc at the northeastern and southeastern regions of the field. High reflection amplitudes (bright spots) signifying hydrocarbon accumulation are also revealed on seismic attribute maps with surrounding shale diaper as the source rock. This study has revealed the prospect (i.e., existence of active petroleum system of probable economic value) of the delineated field in the Niger Delta depobelt.

“Seismic attributes and reservoir simulation’ application to image the shallow-marine reservoirs of Middle-Eocene carbonates, SW Pakistan”

Carbonates form brilliant stratigraphic traps. The execution of traditional seismic data interpretation using time and depth mapping generates ambiguities in the discrimination of porous and non-porous reservoir beds. In these stratigraphic circumstances, placement of development wells within the unproven prospects is a trial for exploration geophysicist. The 3D post-stack seismic attributes and quantitative seismo-petrophysical simulation (QSPS) are applied on Habib Rahi Limestone (HRL) Member from a gas field, SW Pakistan. 45 Hz spectral magnitude delineates the lithology, fractures, and geomorphology of gas-bearing shoal reservoir facies than full-spectrum seismic tools. 45 Hz predicts a north-east oriented gas-bearing stratigraphic lead, which covers an area of 105 km2. The QSPS reveals a very low-density (2–2.1 g/c.c.) and low-velocity (~2500–3000 m/s) of shoal reservoir. The high-quality shoal limestone reservoirs of HRL with ~30% porosity are deposited during the regression phase of sea-level fall in the east. The low-quality fine-grained seal facies with <9% porosity are deposited during the substantial transgression phase of sea-level rise in the west. The cross plots of seismic-based porosity (%) versus inverted velocity (m/s), inverted density (g/c.c), and reservoir thickness (m) show correlation coefficients of (R)2>0.92, (R)2>0.97, and (R)2>0.89. The coarse-grained gas-bearing reservoirs experience 31.8 m thickness and least density (2–2.1 g/c.c.) are deposited during sea-level fall. The 31.3 m thick and high-density (2.2–2.3 g/c.c.) fine-grained seal facies are deposited during sea-level rise. This workflow can serve as an analogue for the development of carbonate fairways within Asia and similar world basins.

Application of pre-stack simultaneous inversion on the reservoir identification and fluid prediction: A case history of Es2 member reservoir in Shengli Oilfield

Es2 member reservoir of Guojuzi sag is located in the east Bohai Bay Basin in China, mainly composed of beach bar sediments, which are thin and in irregular distribution. Conventional post-stack seismic attributes cannot predict the reservoir effectively, while pre-stack seismic inversion also has difficulties in application for the low SNR seismic data. A number of amplitude preserved processes are taken to obtain high SNR seismic data. Then AVA simultaneous inversion is adopted to achieve elastic parameters. Well log analysis shows that µρ and lower Vp/Vs can be good indicators for our target reservoir, therefore we extract µρ and Vp/Vs attribute sections and slices from the result of AVA simultaneous inversion and have successfully delineate the spatial distribution of Es2 member reservoir, which are in consistent with the known well log data.

Using Multiazimuth Seismic Data for Anisotropy Estimation in an Unconventional Reservoir

Productivity of a well in an unconventional reservoir is governed by various static and dynamic reservoir characteristics. Many of these characteristics have proxies among pre and post stack seismic attributes that can be derived from Multiazimuth 3D Seismic Data. The task of a geoscientist in this kind of reservoir is to understand these proxies to predict production behaviour. Natural fracture density and azimuth, as well as horizontal stress azimuth are the key attributes that seismic can help predict. Seismic Velocity and Amplitude variations with azimuth can be used to predict fracture strike, relative fracture density and define potential structural sweet spots. Azimuthal data from a Multiazimuth 3D seismic survey in the Nappamerri Trough of Cooper Basin has been interpreted to estimate fracture intensity and orientation. Co-rendered structural maps are used to create stress maps for different interval of interest. Stress maps help to identify areas of higher anisotropy and areas of lower minimum horizontal stress and so facilitate optimised well placement. To test the geological significance of these maps, correlation of stress vectors against well Image log and cross dipole sonic data was completed. This ground truth validates the prediction of direction and distribution of reservoir fractures based on full azimuth seismic data in this area.

Carbonate fractured gas reservoir prediction based on P-wave azimuthal anisotropy and dispersion

Carbonate fractured gas reservoir detection is very significant for the process of oil-gas exploration. It is difficult to characterize the reservoirs properly by traditional post-stack seismic attributes, because of the complexity of mineralogical composition and fluid type. Based on rock physics, it becomes possible to effectively solve this problem. In this paper, we combine seismic azimuthal anisotropy analysis and P-wave (primary wave) dispersion inversion based on the appropriate rock physics model in order to provide a method for carbonate fractured gas reservoir prediction. Firstly, referring to the geology and logging data of a carbonate fractured reservoir in the S area of Tarim basin in western China, we introduce the Voigt–Reuss–Hill theory into the Chapman model and set up an appropriate model which includes the influences of lithology and physical and fluid properties. Then, through seismic forward modeling and inversion based on this model, we find that attenuation azimuthal anisotropy is very sensitive to fracture density, and P-wave dispersion is closely linked to fluid type. By comprehensive analysis of these two attributes, we can characterize the reservoirs well. Finally, both attributes were applied to analysis of seismic field data for carbonate gas reservoir discrimination in the S area of the Tarim basin. The results show that zones with strong attenuation anisotropy and intense P-wave dispersion are likely to be favorable gas reservoirs. This is consistent with trial production data, hence demonstrating the great advantages of our method in carbonate gas exploration.

Integrated detection of fractures and caves in carbonate fractured-vuggy reservoirs based on seismic data and well data

Aiming at the prediction of carbonate fractured-vuggy reservoirs, we put forward an integrated approach based on seismic and well data. We divide a carbonate fracture-cave system into four scales for study: micro-scale fracture, meso-scale fracture, macro-scale fracture and cave. Firstly, we analyze anisotropic attributes of prestack azimuth gathers based on multi-scale rock physics forward modeling. We select the frequency attenuation gradient attribute to calculate azimuth anisotropy intensity, and we constrain the result with Formation MicroScanner image data and trial production data to predict the distribution of both micro-scale and meso-scale fracture sets. Then, poststack seismic attributes, variance, curvature and ant algorithms are used to predict the distribution of macro-scale fractures. We also constrain the results with trial production data for accuracy. Next, the distribution of caves is predicted by the amplitude corresponding to the instantaneous peak frequency of the seismic imaging data. Finally, the meso-scale fracture sets, macro-scale fractures and caves are combined to obtain an integrated result. This integrated approach is applied to a real field in Tarim Basin in western China for the prediction of fracture-cave reservoirs. The results indicate that this approach can well explain the spatial distribution of carbonate reservoirs. It can solve the problem of non-uniqueness and improve fracture prediction accuracy.

Seismic attribute analysis for fracture detection and porosity prediction: A case study from tight volcanic reservoirs, Barmer Basin, India

The Raageshwari Deep Gas Field is situated in the southern part of the onshore Barmer Basin in Rajasthan, India. The field contains gas condensate with excellent gas quality reservoired dominantly within the tight volcanic rocks. Optimal development and production of the tight reservoirs requires characterization of faults and natural fractures that are important to fluid flow and production. Reservoir quality of the volcanic complex is governed by the distribution of matrix pore spaces and fractures. Use of seismic attributes for detecting effective reservoir pore spaces such as fractured zones and vesicles is challenging considering the limits of seismic resolution in the tight volcanic reservoirs. Poststack seismic attributes used in this study for fracture detection include geometric attributes such as coherency for detection of seismically resolved faults and reflection curvature attributes for discrimination of subseismic faults. Discrete frequency components extracted from seismic data are also used to analyze geologic discontinuities. Besides geometric attributes, seismic wave attenuation from the basic instantaneous seismic attributes — instantaneous amplitude, phase, and frequency — are also key indicators of fractured zones and vesicles that create effective pore spaces. In fractured intervals within the volcanic reservoirs, a decrease in density and slowdown in acoustic propagation velocity yields a relative drop in P-wave impedance, which are important characteristics to determine fractured zones. Detected fractured zones from seismic attributes were validated with wells, image logs, and production data. In addition to fracture detection, predicting subsurface properties, such as porosity distribution away from wells, has always been a fundamental requisite for appropriate infill well planning. Full-azimuth seismic data and selected seismic attributes were used in multiattribute analysis to predict porosity and were correlated with “blind” wells. This study captures the heterogeneous volcanic rock porosity distribution in the field, improving the understanding of varied production behavior observed within the volcanic rock complex.

Integration of core data, well logs and seismic attributes for identification of the low reservoir quality units with unswept gas in the carbonate rocks of the world’s largest gas field

Tight zones of the gas bearing Kangan and Dalan formations of the South Pars gas field contain a considerable amount of unswept gas due to their low porosity, low permeability and isolated pore types. The current study, integrates core data, rock elastic properties and 3D seismic attributes to delineate tight and low-reservoir-quality zones of the South Pars gas field. In the first step, the dynamic reservoir geomechanical parameters were calculated based on empirical relationships from well log data. The log-derived elastic moduli were validated with the available laboratory measurements of core data. Cross plots between estimated porosity and elastic parameters based on Young’s modulus indicate that low porosity zone coincide with high values of Young’s module. The results were validated with petrographic studies of the available thin sections. The core samples with low porosity and permeability are correlated with strong rocks with tight matrix frameworks and high elastic values. Subsequently, rock elastic properties including Young’s modulus and Poisson’s ratio along with porosity were estimated by using neural networks from a collection of 3D post-stack seismic attributes, such as acoustic impedance (AI), instantaneous phase of AI and apparent polarity. Distinguishing low reservoir quality areas in pay zones with unswept gas is then facilitated by locating low porosity and high elastic modulus values. Anhydrite zones are identified and eliminated as non-pay zones due to their characterization of zero porosity and high Young modulus values. The methodology described has applications for unconventional reservoirs more generally, because it is able to distinguish low porosity and permeability zones that are potentially productive from those unprospective zones with negligible reservoir quality.

Facies analysis by integrating 3D seismic attributes and well logs for prospect identification and evaluation — A case study from Northwest China

Characterization of facies within a hydrocarbon reservoir is essential for potential prospect identification and evaluation. We have developed a practical workflow that integrates poststack seismic attributes and well-log facies analysis to understand the development and depositional setting of the Triassic-age Akekule Formation in Tahe field, Northwest China. The workflow begins with sequence and sedimentary cycle analysis on selected benchmark wells. We then identify sand bodies within each sedimentary cycle using well logs. The analysis from well logs and drilling cuttings together illustrate that there exist five sand bodies within the fourth member of Akekule Formation. We next predict the horizontal distribution of each sand body based on the facies analysis on well logs. We finally perform multiple poststack seismic attributes analyses to identify seismic facies. Multiattribute analysis is implemented either through corendering multiple seismic attributes or neural network clustering on multiple seismic attributes. The lithofacies obtained from seismic attribute analysis is calibrated with facies identified using well logs.

Interpretation of fractured zones using seismic attributes — Case study from Teapot Dome, Wyoming, USA

We have used poststack seismic attributes to describe the fracture network of the naturally fractured Tensleep Formation at Teapot Dome, Wyoming, USA. The attributes include coherence, coherence based on spectral decomposed seismic data, attributes based on curvature, and textural attributes based on the gray-level co-occurrence matrix (GLCM). Results were compared with image log interpretations of four wells. Seismic attribute analysis allowed determination of strikes and dips as well as the intensity of fractures. The GLCM-based attributes proved especially valuable for building a discrete fracture network.

3D seismic attributes and well-log facies analysis for prospect identification and evaluation: Interpreted palaeoshoreline implications, Weirman Field, Kansas, USA

Abstract We present a workflow integrating post-stack seismic attributes and well-log facies analysis in order to understand the development history and depositional setting of the Weirman Field in central Kansas, and to propose a fresh prospect-evaluation approach for our study area. This study successfully addresses compartmentalisation due to highly variable lithofacies by analysing geophysical well-logs, lithofacies modelling, and 3D seismic attributes including time thickness, amplitude, and structural time maps. In the light of some discouraging drilling results at Weirman Field, we recommend a revised approach to prospect evaluation, based upon a newly interpreted palaeodepositional setting, to predict the distribution of clean sand facies, using a combination of seismic attribute signatures and structural closure maps. In support of our interpretation, we compare the proposed palaeodepositional setting with a modern analogue of a transitional coastal to shallow marine depositional environment. The dimensions and spatial relationships of the interpreted geo-bodies are in conformity with the modern shoreline analogues of a barrier beach or strandplain adjacent to an estuary. The lithofacies clustering was calibrated to a lithostratigraphic column, which was constructed based on drilling-cuttings of Wanda Judeen No. 1. This calibration was upheld against correlation with well-logs for other wells.

Characterization of a fracture zone using seismic attributes at the In Salah CO2 storage project

The In Salah carbon dioxide storage project in Algeria has injected more than 3 million tons of carbon dioxide into a water-filled tight-sand formation. During injection, interferometric synthetic aperture radar (InSAR) reveals a double-lobed pattern of up to a 20-mm surface uplift above the horizontal leg of an injection well. Interpretation of 3D seismic data reveals the presence of a subtle linear push-down feature located along the InSAR determined surface depression between the two lobes, which we interpreted to have to be caused by anomalously lower velocity from the fracture zone and the presence of [Formula: see text] displacing brine in this feature. To enhance the seismic interpretation, we calculated many poststack seismic attributes, including positive and negative curvatures as well as ant track, from the 3D seismic data. The maximum positive curvature attributes and ant track found the clearest linear features, with two parallel trends, which agreed well with the ant-track volume and the InSAR observations of the depression zone. The seismic attributes provided a plausible characterization of the fracture zone extent, including height, width, and length (80, 350, and 3500 m, respectively), providing important information for further study of fracture behavior due to the [Formula: see text] injection at In Salah. We interpreted the pattern of depression between two surface-deformation lobes as caused by the opening of a subvertical fracture or damage zone at depth above the injection interval, which allowed injected [Formula: see text] to migrate upward. Our analysis corroborated previous interpretation of surface uplift as due to the injection of [Formula: see text] in this well.