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Shallow stratigraphy in Southern Oman is characterized by the presence of an anhydrite layer (RUS formation) causing a strong velocity inversion which makes seismic imaging particularly difficult. This known shallow sharp velocity inversion cannot be easily captured with methods relying on reflection or diving wave energy.
We propose here to use multi-wave inversion using first breaks and dispersion curves of surface waves to provide near-surface high resolution velocity models in the shallow range depths (0-400m). The success of Multi-Wave Inversion strongly depends on the reliability of the surface wave velocity picking, which could be much more challenging compared to the conventional first break picking. Heavy preconditioning is often the solution to increase dispersion curves quality and to obtain a narrower velocity corridor. To improve reliability, we use K-means clustering, an unsupervised machine learning method (
The multi-wave inversion, fed with the optimized phase velocity picks, captures the shallow velocity inversion, which is impossible to recover with either first break tomography only or diving wave full waveform inversion only. The combination of two recently developed technologies allows us to characterize accurately the near surface for the first time in the South of Oman. The velocity inversion caused by the RUS formation is well captured and the velocity trend of the updated model follows correctly the checkshot trend down to 500m, confirming the reliability of the dispersion curves picks at a very low frequency. By incorporating this shallow inversion layer into the velocity model, the resulting seismic image is significantly improved and more interpretable. Geological features such as faults appear clearly and seismic layering in the tilted blocks is significantly improved with the multi-wave Inversion machine learning-guided workflow.
Parasequence thickness and frequency are traditionally interpreted to be controlled by allocyclic processes such as oscillations in eustatic sea-level. However, the use of numerical forward models is challenging these concepts. Outcrop data from Ras Al-Khaimah (UAE) were incorporated into numerical forward models and used to replicate parasequences from the Upper Kharaib Reservoir Unit. Results indicate that clinoform geometries within the parasequences can form by autocyclic, rather than allocyclic, processes.
Stratigraphic, sedimentological and palaeoenvironmental interpretations made from outcrops of Upper Kharaib carbonate clinoform parasequences at Wadi Rahabah, Ras Al-Khaimah, were used to build a numerical stratigraphic forward model. Numerical stratigraphic forward models produce fully quantitative three-dimensional deterministic models that replicate and predict the spatial distribution of stratal geometries, stacking patterns, sedimentary thickness and facies formed under a set of predefined input parameters and boundary conditions. A CarboCAT numerical model of carbonate deposystems that uses cellular automata to determine the distribution and lithofacies of heterogeneous carbonate strata in three dimensions (
Results of the numerical forward model show that carbonate clinoform parasequences from the Upper Kharaib Reservoir Unit can be generated by an autocyclic Ginsburg-type mechanism of sediment transport and shoreline progradation (e.g.
Observations from numerical forward models have implications for the distribution of reservoir intervals within the Upper Kharaib. Parasequences formed by autocyclic process produce heterogeneous reservoirs with complex facies mosaics. Lateral heterogeneity and variable thicknesses within these reservoirs is more difficult to correlate and trace across fields than simple stacked, layer cake, parasequences created by sea-level oscillations.
Copyright 2020, International Petroleum Technology Conference This paper was prepared for presentation at the International Petroleum Technology Conference held in Dhahran, Saudi Arabia, 13 - 15 January 2020. This paper was selected for presentation by an IPTC Programme Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the International Petroleum Technology Conference and are subject to correction by the author(s). The material, as presented, does not necessarily reflect any position of the International Petroleum Technology Conference, its officers, or members. Papers presented at IPTC are subject to publication review by Sponsor Society Committees of IPTC. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of the International Petroleum Technology Conference is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of where and by whom the paper was presented.
High fidelity seismic amplitude reconstruction through pre-stack migration is crucial for accurate elastic inversion. Despite a relatively flat geology of the Abu Dhabi region, accurate imaging is required for a stable elastic inversion. This can be challenging because the main reservoir Arab lies underneath the strongly anisotropic overburden of the Nahr Umr formation. In this case study, we show how we effectively addressed this challenge through PSDM.
With PSDM imaging, we have overcome the challenges of complex ray paths passing through the strongly anisotropic Nahr Umr layer and the rapid lateral velocity variation in the Mishrif formation. Evidently, the success of PSDM relies strongly on the accuracy of the depth velocity model used. To achieve this we adopt different forms of tomographic inversion, for example, using 3D non-linear slope tomographic inversion, where velocity and anisotropy (Epsilon) models are jointly inverted. Additionally, short wavelength velocity variations caused by the Mishrif interval are resolved through structurally-constrained tomography (SCT).
The superiority of PSDM imaging over PSTM in reconstructing AVA compliant seismic amplitudes is demonstrated on an ocean bottom survey from the transition zone offshore Abu Dhabi. Fast-track AVA elastic inversion is used to assess the benefit of PSDM imaging over PSTM. With a more stable Vp/Vs ratio and smaller inversion residual, PSDM imaging demonstrates a greater accuracy in reconstructing the pre-stack seismic amplitude and thus are more appropriate for estimating elastic reservoir properties.
The value of PSDM imaging for better understanding of reservoir characteristic has been well demonstrated in this case study from the Abu Dhabi transition zone, thus optimizing the value of the acquired seismic data for asset development.
Dragon Oil (ENOC Group) is operator with 100 % of interest in the exploration East Zeit Bay (EZB) block, which covers a surface of 93 km2 in an area where producing oil fields are nearby; e.g.: East Zeit, Hilal, Ashrafi, Ashrafi SW, and Zeit Bay fields. The license commitment consists of a seismic acquisition and processing and the drilling of two exploration wells before September 18th, 2019, which corresponds to the end of the extension of the first exploration period. The EZB block is located in the Gulf of Suez (GoS) in an area characterized by very shallow waters, where two coral reef islands emerge during low tide and several obstacles are present, i.e.: an oil terminal, mooring buoys, a waiting area for tankers and fishing and touristic activity. In the period 1969-1984, some 240 km of 2D seismic were acquired within the block using different acquisition parameter sets and processed with inhomogeneous flow-charts generating a sparse 2D seismic grid of variable data quality. Some of these data were reprocessed even in PSTM and PSDM, but without any sensible improvement. Furthermore, 3D seismic surveys were also acquired in 1996/1997 and almost cover the entire surface of the EZB block: The Ashrafi Deep Water (DW) survey, obtained towing a streamer, has been recorded in the north-eastern part of the block and the central and western parts have been surveyed by the West Ashrafi campaign in Ocean Bottom Cable (OBC) mode. But this 3D is of very poor quality due to the screening effect of coral covering the sea bottom on the geophone component of the recording.
During the last four years, extensive multidisciplinary analyses integrating reprocessing of existing magnetic data with new acquired gravity data and new and reprocessed 2D and 3D seismic data, well log and dipmeter analyses were carried out by Dragon Oil to delineate drillable prospects. Key of the success in generating a valid interpretation was the idea to combine a well site survey, compulsory for rig location, with a 2D seismic survey in an area with restricted vessel maneuverability.
Low fold poorly sampled vintage seismic data often suffers from poor fault imaging. This can have a critical impact on reserve estimation and well planning. Acquiring high density seismic data over producing fields requires overcoming logistic challenges along with additional costs and increased acquisition time. However, advances in seismic processing technology could improve the fault resolution of vintage seismic data in a cost effective manner. This has been proven in a case study from offshore Abu Dhabi.
The presence of strong surface wave energy, resulting from the shallow water environment and near surface heterogeneity, masked events in the deeper part of the section. Poor and irregular spatial sampling caused aliasing of the surface wave. In the vintage processing, strong de-noising was applied to tackle the aliasing issue, which smeared the fault definitions. During the re-processing, a joint low-rank and sparse inversion was applied to regularize and densify the input data to obtain a de-aliased surface wave noise model. Subsequent adaptive subtraction of the noise from the input removed strong surface waves without damaging the body waves.
The stack quality was improved by application of cascaded surface wave attenuation algorithms. Additional five dimensional Fourier reconstructions of the data improved the signal quality. A carefully designed fault-preserving residual noise attenuation workflow further reduced the residual noise content. Automatic picking of key stratigraphic horizons was carried out in order to evaluate the spatial resolution of the re-processing outcome. Sharper discontinuities along fault planes observed compared to the interpretation of the vintage seismic data. Increased confidence in fault interpretation is of value for structural restoration study and further reservoir understanding. In addition, several new, previously not-visible, small fault features were highlighted as evident from volumetric curvature and semblance analysis. They have been effectively utilized in a forthcoming drilling campaign to de-risk well operation.
Multi-dimensional data densification to de-alias surface waves and five dimensional re-construction of the signal proved to be beneficial to enhance the fault features on the poorly sampled seismic data.
This paper outlines methods to characterize hydraulic fracture geometry and optimize full-scale treatments using knowledge gained from Diagnostic Fracture Injection Tests (DFITs) in settings where fracturing pressures are high.
Hydraulic fractures, whether created during a DFIT or larger scale treatment, are usually represented by vertical plane fracture models. These models work well in a relatively normal stress regime with homogeneous rock fabric where fracturing pressure is less than the Overburden (OB) pressure. However, many hydraulic fracture treatments are pumped above the OB pressure, which may be caused by near well friction or tortuosity but, may also result in more complex fractures in multiple planes.
Procedures are proposed for picking Farfield Fracture Extension Pressure (FFEP) in place of conventional ISIP estimates while distinguishing between storage, friction and tortuosity vs. fracture geometry indicators.
Analysis of FFEP and ETFRs identified in the DFIT PTA analysis method combined with the context of rock fabric and stress setting are useful for designing full-scale fracturing operations. A DFIT may help identify potentially problematic multi-plane fractures, predict high fracturing pressures or screen-outs. Fluid and completion system designs, well placement and orientation may be adjusted to mitigate some of these effects using the intelligence gained from the DFIT early warning system.
This paper outlines methods to characterize hydraulic fracture geometry and optimize full-scale treatments using knowledge gained from Diagnostic Fracture Injection Tests (DFITs) in settings where fracturing pressures are at or above the overburden gradient.
Hydraulic fractures, whether created during a DFIT or a larger scale treatment, are usually represented by vertical plane fracture models. These models work well in a relatively normal stress regime with homogeneous rock fabric where fracturing pressure is less than the Overburden (OB) pressure. However, many hydraulic fracture treatments are pumped above the OB pressure. This high pressure may be caused by near well friction or tortuosity but may also be the result of more complex fractures in multiple planes.
Procedures are proposed for picking Farfield Fracture Extension Pressure (FFEP) in place of conventional IIP estimates while distinguishing between storage, friction and tortuosity vs. fracture geometry indicators. Analysis of FFEP and ETFRs combined with the context of rock fabric and stress setting are useful for designing full-scale fracturing operations. A DFIT may help identify potentially problematic multi-plane fractures, predict high fracturing pressures or screen-outs. Fluid and completion system designs, well placement and orientation may be adjusted to mitigate some of these effects using the intelligence gained from the DFIT early warning system.
A flow simulation-driven time-lapse seismic feasibility study is performed for the Amberjack field that leverages existing multi-vintage 4D time-lapse seismic data. The focus is a field consisting of stacked shelf and deepwater reservoir sands situated in the Gulf of Mexico in Mississippi Canyon Block 109 in 1,030 ft of water. The solution leverages seismic interpretation, seismic inversion, earth modeling, and reservoir simulation [including embedded petro-elastic modeling (PEM) capabilities] to enable the reconciliation of data across multiple seismic vintages and forecast the optimal future seismic survey acquisition in a closed-loop. The overarching feasibility solution is integrated and simulation-driven involving multi-vintage seismic inversion, spatially constraining the petrophysical property model by seismic inversion, and performing reservoir simulation with the embedded PEM. The PEM is used to compute P-impedance and Vp/Vs dynamically, which enables tuning to both historical production and multi-vintage seismic data. The process considers a hybrid fine-scale 3D geocellular model in which the only upscaling of petrophysical properties occurs when the P-impedance from seismic inversion is blocked to the 3D geocellular grid. This process minimizes resampling errors and promotes direct tuning of the simulator response with registered seismic that has been blocked to a geocellular earth model grid. The results illustrate a three-part simulation-to-seismic calibration procedure that culminates with a prediction step which leads to a simulation-proposed time-lapse seismic acquisition timeline that is consistent with the calibrated reservoir simulation model. The first calibration tunes the model to historical production profiles. The second calibration reconciles the dynamic P-impedance estimate of the simulated shallow reservoir with that of the seismic inversion blocked to the 3D geocellular grid. The combination of these two steps outline a seismic-driven history matching process whereby the simulation model is not only consistent with production data but also the subsurface geologic and fluid saturation description. Large and short wavelength disparities in the P-impedance calibration existing between the simulator response and the time-lapse seismic data are attributed to resampling errors as a result of seismic inversion-derived P-impedance being blocked to the 3D geocelluar grid, as well as sparse well control in the earth model which leads to the obscuring of some asset-specific characteristics. The results of the third calibration step show how the time-lapse seismic feasibility solution accurately confirms prior seismic surveys undertaken in the asset. Given this confirmation, the solution achieves a suitable prediction of seismic-derived rock property response from the reservoir simulator as well as the optimal future time-lapse seismic acquisition time.
Swami, Vivek (CGG) | Tavares, Julio (CGG) | Pandey, Vishnu (CGG) | Nekrasova, Tatyana (CGG) | Cook, Dan (Bravo Natural Resources) | Moncayo, Jose (Bravo Natural Resources) | Yale, David (Yale Geomechanics Consulting)
In this study, a state-of-the-art seismic driven 3D geological model was built and calibrated to a petrophysical and geomechanical analysis, 1D-MEM (Mechanical Earth Model), on chosen wells within the Arkoma Basin of Oklahoma. The well information utilized in this study included basic wireline logs and core analysis, including XRD (X-Ray diffraction) data. The traditional petrophysical analysis was augmented with advanced rock physics and statistical techniques to generate the necessary logs. Hydrostatic, overburden and pore pressures were calculated with a petrophysical evaluation model. The 1D-MEMs were based on the Eaton/Olson/Blanton approach with the HTI (Horizontal Transverse Anisotropy) assumption. The 1D-MEMs were calibrated to laboratory data (triaxial tests) and field observations (mud logs, wellbore failure, frac pressures). Therefore, a very good confidence was achieved on Biot's coefficient, tectonic components, anisotropy and dynamic to static conversion factors for Young's Modulus and Poisson's Ratio. Seismic inversions were performed in different time windows and merged to generate high resolution P- and S-Impedance attributes from surface down to the target interval after careful AVO compliant gather preconditioning. A density volume estimate was calibrated to well data, accounting for different geological formations, to decouple P- and S-Wave components as a 3D volume, as well as dynamic Young's modulus (E) and Poisson's ratio (PR). Dynamic E and PR were converted to static parameters using results from 1D-MEMs; and 3D models of Biot's coefficient (α) and tectonic components were built to compute 3D fracture pressure volumes calibrated to well data. The final products were seismic-driven 3D pore pressure and fracture pressure calibrated to 1D-MEMs. The correlation between measured/estimated well logs and corresponding seismic-derived pseudo logs was more than 80%, which indicates good quality of seismic inversion results and hence 3D-MEM. Also, stress barriers, anisotropy, and brittleness indices were calculated on well scale which would help to identify best zones to place hydraulic fractures. The 3D geological model will aid in identifying sweet-spots and optimizing hydraulic fractures.