Tool For Reservoir Characterization Research Articles

Building initial model for seismic inversion based on semi‐supervised learning

AbstractSeismic inversion is an important tool for reservoir characterization. The inversion results are significantly impacted by a reliable initial model. Conventional well interpolation methods are not able to meet the needs of seismic inversion for lateral heterogeneous reservoirs. Inspired by the sequence modelling network and seismic inversion in the Laplace–Fourier domain, we propose an initial model‐building method using semi‐supervised learning strategy. The proposed method considers spatial information to ensure the horizontal continuity of the initial model. Based on the fact that the low‐frequency components of seismic signals in the Laplace–Fourier domain are easier to obtain, we use the forward model in the Laplace–Fourier domain to replace the time‐domain forward model. The proposed workflow was validated using the Marmousi II model. Although the training was carried out on a small number of low‐frequency impedance traces, the proposed workflow was able to build low‐frequency model for the entire Marmousi II model with a correlation of 98%. Field data examples demonstrate the feasibility and effectiveness of the proposed method. For lateral heterogeneous reservoirs, the proposed method performs better than the well interpolation method. By utilizing the model obtained by the proposed method as the initial low‐frequency model of the conventional inversion method, it is possible to estimate better inversion results. The results of different combinations of training sets demonstrate the stability of the proposed method. This method may still be a viable choice if there is lateral heterogeneity underground but not much well‐logging label data.

Technology Focus: Well Testing (February 2024)

Standing alone as the shortest month of the year, February also features JPT’s Well Testing Technology Focus, reviewing the latest industry publications on the subject. Well testing has enjoyed a recent uptick in activity and interest as operators continually realize the value in understanding and monitoring the dynamic performance of their reservoirs. Whether it pertains to the deliverability of conventional oil and gas or the storage potential for carbon capture and storage, large-scale dynamic data remains one of the more coveted pieces to the subsurface puzzle. There is no silver bullet for reservoir characterization. Instead, proper characterization will always be the result of integrating static and dynamic data, collected at varying scales, with a macro geological understanding. Technology facilitates the collection of the aforementioned data. With the latest technologies pushing limits of what can be achieved, subsurface engineers must rigorously evaluate what reservoir characterization techniques and tools are suited for project objectives. Formation testing (FT) platforms provide many options for operators to get a first look at dynamic reservoir performance and nearly always precede a well test. After digesting the alphabet soup of acronyms, so many FT options exist that one may encounter what psychologists refer to as “choice overload.” FT objectives also may begin to overlap with objectives traditionally reserved for drillstem tests (DSTs), narrowing a long-standing technology gap. The current advances in FT tools are exciting, and using FT tools to perform a “mini-DST” makes for brilliant marketing. However, “mini” could mean up to 10,000 times less produced volume, which undoubtedly affects objectives thought to overlap. Subsurface complexity is mitigated by defining clear objectives and executing data-collection programs to reduce uncertainty. Caution should be taken in selecting how to dynamically test your reservoirs. Regardless of how advanced hardware becomes, achievable objectives always will be dependent on key factors such as rock and fluid properties, reservoir geometry, and local regulatory and environmental considerations. This month’s papers highlight ongoing developments from different segments of the well-testing discipline. Dive into valuable lessons learned from a frontier carbon capture, use, and storage project, backed by an impressively sized data set and an in‑depth review of multiphase effects. This case study covers differing saturations around the wellbore region and fluid types in operations and should have global applications. Learn about the limitations and potential pitfalls of nonisothermal effects in pressure transient analysis, which pose challenges in the reservoir characterization of geothermal wells. Sensitivities to thermal effects on reservoir rock properties provide intriguing insights. Completion efficiency also may be affected by thermal effects, resulting in additional pressure drop at sandface. Finally, catch up on one of the weapons most recently added to the well-testing arsenal with powerful new FT tools that feature industry improvements for greater flexibility and improved data reliability. Recommended additional reading at OnePetro: www.onepetro.org. OTC 32610 Multiphase Flowmeter Comparison in a Complex Field by Mohammed Alqahtani, Saudi Aramco, et al. IPTC 23050 Frequently Asked Questions in the Interval Pressure Transient Test and What Is Next With Deep Transient Test by Saifon Daungkaew, SLB, et al.

Improved methodology development for assessing the reservoir collector properties by the quantitative reservoir characterization tools

The object of research in the paper is the process of fluid transfer through the pore space of the reservoir rock. In this paper, using an expert method, the shortcomings of the Ukrainian methodology for assessing the reservoir properties of the reservoir were highlighted. In particular, the sources of uncertainty accumulation in determining the absolute values of the reservoir's filtration parameters have been identified. The existing problem is that the algorithms of actions, which are the basis of the Ukrainian method of assessing reservoir properties, introduce a significant degree of uncertainty into the assessment results. In order to reduce uncertainty, the introduction of the concept of a representative elemental volume is considered when conducting laboratory research and the construction of a three-dimensional digital model of this elementary volume. It is suggested to improve the Ukrainian method of assessing the collector properties of the deposit based on current Western research. It was established that the standard methods of assessing the reservoir properties of the deposit are a source of accumulation of uncertainty in the development of technological documentation for the development of the deposit. The work is aimed at the development of an improved methodology for assessing the collector properties of the deposit. It is proposed to add to the action algorithm the stage of determining the representative volume of the sample, building its three-dimensional model, and digitizing it. At the final stage, the connectivity of the pores inside the sample is determined using the Minkowski function to improve the quality of the project documentation for the development of deposits. Guidelines have been developed to improve standard methods for assessing the collector properties of the deposit. The use of an improved methodology for assessing the reservoir properties of the deposit leads to a significantly lower degree of uncertainty and helps to form a more reliable picture of the operation of the reservoir at the design stage of its development. The presented study will be useful for the engineering personnel of foreign contractor companies, as it justifies the need to collect additional core material and sets the quality criteria of the information obtained about the collector properties of the deposit.

Fault characterization and flow barrier detection using capacitance-resistance model and diagnostic plots

Advantageous for its speed and far less data requirements, the Capacitance-Resistance Model has been successfully applied to waterflood performance prediction and optimization, gas flood optimization and reservoir characterization. In this study, a diagnostic plot and an iterative workflow that incorporates geological and well data with calibrated CRM results, were developed for depicting injector-producer communication, thereby characterizing a reservoir of interest. These were validated using three synfield cases. Thereafter, two selected faults in a Far East Oil Field (FEOF) were characterized and sealing baffles identified around these faults. Based on the results, one fault had several sections with varying degrees of communication and sealing baffles on either side of the fault. The second fault was mostly sealing with no sealing baffles on either side. The new diagnostic plot and workflow also quality-checked interwell connectivities from calibrated CRM, thereby substantially improving the fault characterization process. With far fewer and readily available data from oilfields, reduced physics models like CRM and the Diagnostic Plots are tools for cost-effective and speedy reservoir characterization, and to corroborate results of Interference and Tracer Tests, as well as 4D Seismic.

Using rock-physics models to validate rock composition from multimineral log analysis

Multimineral log analysis is a quantitative formation evaluation tool for geologic and petrophysical reservoir characterization. Rock composition can be estimated by solving equations that relate log measurements to the petrophysical endpoints of minerals and fluids. Due to errors in log data and uncertainties in petrophysical endpoints of constituents, we have used effective medium models from rock physics as additional independent information to validate or constrain the results. We examine the Voigt-Reuss (VR) bound model, self-consistent approximation (SCA), and differential effective medium (DEM). The VR bound model provides the first-order quality control of multimineral results. We first show a conventional carbonate reservoir study with intervals in which the predicted effective medium models from multimineral results are inconsistent with measured elastic properties. We use the VR bound model as an inequality constraint in multimineral analysis for plausible alternative solutions. The SCA and DEM models provide good estimates in low-porosity intervals and imply geologic information for porous intervals. Then, we present a field case of the Bakken and Three Forks formations. A linear interpolation of the VR bound model helps validate multimineral results and approximate the elastic moduli of clay. There are two major advantages to using our new method: (1) Rock-physics effective medium models provide independent quality control of petrophysical multimineral results and (2) multimineral information leads to realistic rock-physics models.

New insight of correlation between digital rock analysis and petrographic study for rock type classification within carbonate reservoir transition zone

The characterization of capillary transition zone (TZ), which contains large amount of oil, is challenging, because of the rock types in it affecting the fluid flow behavior. The thickness of TZ may vary from a few feet to hundreds of feet, spanning extremely low permeability and very high permeability reservoirs. Conventional core analysis (CCA) and special core analysis (SCAL) techniques can be used to study and model TZs, but the detailed pore structure information governing the rock properties rarely can be obtained. Digital rock analysis (DRA) technique can directly capture the images of rock microstructures and accurately simulate the rock properties based on digital rock images. Consequently, DRA technique can be well used for reservoir characterization. In this paper, thin sections (TS), scanning electron microscope (SEM) images, and X-Ray computed tomography (XCT) scans are used to study the rock properties for reservoir characterization. The petrography and diagenesis of TZ are also analyzed based on these digital images and simulations. DRA technique is used to simulate the rock properties. The results show that DRA can be well used to predict the rock properties such as porosity and P- and S-wave velocity. The permeability of TZ samples is found to be less than 1 mD. The TZ rock samples are qualitatively and quantitatively classified into three types such as matrix, fractured, and vuggy by an improved carbonate rock index (ICRI) method. These show that DRA is a powerful tool for carbonate reservoir characterization.

Hydrocarbon reservoir characterization of “Otan-Ile” field, Niger Delta

Otan-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.

Practical methodology for interwell tracer applications

Tracer technology has been used in the oil industry to investigate the fluid flow behavior into the reservoir. Using this technology is possible to obtain relevant data from the reservoir such as remaining oil accumulations, estimate volumetric sweep efficiency, define reservoir heterogeneities, identify flow channeling, and determine residual oil saturation (Sor).
 
 This technology has been one of the most useful tools for reservoir characterization for several decades. The tracer is injected in the injector well and then monitored in the producer wells through the tracer concentration measurements. Although many tracer studies have been documented for reservoir characterization, the available information and methodologies related to the design, implementation, and interpretation of tracer tests are limited or confidential.
 The goal of his article is to show a methodology for the design, execution, and interpretation of interwell tracer tests, which includes procedures for field implementation, sampling, and monitoring of these tests. Laboratory analysis using ultra-high-performance liquid chromatography is described in the experimental evaluation of tracer tests. Additionally, for a better understanding of the technology, examples of laboratory and field cases are presented.

A History of Nuclear Spectroscopy in Well Logging

This paper provides a history of nuclear spectroscopy in well logging from its beginnings in 1939 up until the present day. After the invention and implementation of gamma ray logging, this paper traces the technological development of the pulsed-neutron capture (sigma) log, the spectral gamma ray log, the carbon-oxygen log, tracer identification logs, small-diameter reservoir characterization tools, and finally the geochemical log. The key to the science of nuclear spectroscopy has been the detection of gamma rays, their energies, and the identity of their parent atomic nuclei. From this, the properties of the formation can be better understood. There have been many advances in technology that have led to the current state of nuclear spectroscopy tools. The most notable has been the ability to detect the presence of a gamma ray. After this came numerous advances in scintillator crystal detector technology, the pulsed-neutron generator, the energy digitization of gamma ray pulses, fast-timing electronics, and powerful computers. These advances have made possible the complex, gamma ray-centric logging tools that we have today that have helped petroleum engineers in the energy industry locate and produce hydrocarbon, kerogen, and natural gas reservoirs for the benefit of each individual in the world. This paper discusses the rich history of these historic developments.

Synthetic geochemical well logs generation using ensemble machine learning techniques for the Brazilian pre-salt reservoirs

Geochemical logs are an essential tool for hydrocarbon reservoir characterization. The rock composition given by these logs is useful for porosity calculation, stratigraphic modeling, diagenesis estimation, and well acidification. In reduced logging operations performed in carbonate reservoirs of the Brazilian pre-salt, the geochemical tool is no longer acquired, aiming at optimization and cost reduction. This research aims the development of synthetic geochemical logs using machine learning algorithms. The database includes 22 wells with complete logging acquisition, and the input logs are natural gamma-ray, gamma-ray spectroscopy, density, photoelectric factor, neutron porosity, nuclear magnetic resonance, and sonic. The chemical elements chosen as output are Al, Ca, Fe, Mg, Na, Si, S, and Ti. Five models based on machine learning are trained using 19 wells: Support-vector machine, Multilayer perceptron, Random Forest, AdaBoost, and XGBoost. AdaBoost represents the best algorithm because, in addition to showing the best results, it allowed for a more simplified preprocessing and hyperparameter tuning. The evaluation of the models applies R2 and root mean squared error (RMSE) in validation data and cross-validation. Robust models are acquired for Al, Ca, Fe, Mg, Si, S, and Ti, with R2 above 0.80. Na shows R2 slightly above 0.70. All the models have RMSE between 10-2 to 10-4. The most important logs during training are density, photoelectric factor, K, Th, U, and neutron porosity. Synthetic geochemical logs created for three test wells show a good agreement with acquired logs, being able to reproduce general trends of the pre-salt formations. The machine learning model is capable of substituting the acquisition of geochemical logs with high confidence, representing cost reduction, and supplying engineers and geoscientists with quality data to be used in formation evaluation.

Water\u2013rock interactions in the Bruchsal geothermal system by U\u2013Th series radionuclides

Uranium and thorium decay series disequilibria in deep geothermal brines are a result of water–rock interaction processes. The migratory behavior of radionuclides provides valuable site-specific information and can therefore be an important tool for reservoir characterization and sustainable management of geothermal sites. In this study, we present data from long-term monitoring of naturally occurring 238U, 232Th and 235U series radionuclides analyzed in brine samples collected from the Permo-Triassic sedimentary reservoir rock at the Bruchsal geothermal site (SW Germany). The results show that radionuclides of the elements radium (226Ra, 228Ra, 224Ra, 223Ra), radon (222Rn), and lead (210Pb, 212Pb) are rather soluble in brine, while isotopes of uranium (238U, 234U, 235U), thorium (232Th, 228Th, 230Th), polonium (210Po), and actinium (227Ac, 228Ac) have low solubilities and are mostly immobile. Activities of radium isotopes in the geothermal brine exceed those of their thorium progenitors (average 226Ra = 29.9 Bq kg−1, about 103 times that of its 230Th parent). Modelling the observed disequilibria allows the following conclusion on water–rock interaction processes: (1) supply from alpha-recoil depends on isotope half-life because it is limited by the rate of diffusion through microfractures causing isotopic fractionation. (2) Radium retardation due to adsorption is low (226Ra/222Rn = 1.3) resulting in adsorption–desorption rate constants in the order of 10−10 s−1 for k1 and 10−9 for k2. (3) Scavenging of 226Ra from brine can best be explained by co-precipitation with barite resulting in an observed 226Ra anomaly in the solids of the reservoir section. The precipitation rate constant amounts to ca. 3.4 × 10−8 s−1 corresponding to a mean removal time of radium from brine by mineral precipitation to approximately 1 year.

Rock typing and hydraulic flow units as a successful tool for reservoir characterization of Bentiu-Abu Gabra sequence, Muglad basin, southwest Sudan

The present study aims at conducting a detailed reservoir characterization of the Early Cretaceous Bentiu and Abu Gabra formations in Muglad basin which is one of the most prospective hydrocarbon basins in South Kordofan, SW Sudan. This can be achieved through integration between well logging (conventional), petrography (thin sections, and scanning electron microscopy SEM), and core data.Based on this integrated study, the Abu Gabra-Bentiu sequence is composed of two reservoir rock types (RRTs). RRT1 is composed of quartz arenite, whereas RRT2 is composed of quartz wacke. The best storage and flow capacities and the best reservoir quality are assigned for RRT1 due to its good to excellent porosity (20.0 ≤ ∅ ≤ 34.1%), permeability (138 ≤ k ≤ 4140 md), reservoir quality index (0.61 ≤ RQI ≤ 2.91 μm), and flow zone indicator (2.37 ≤ FZI ≤ 6.12 μm) values. This rock type is mostly assigned to two hydraulic flow units (HFU-1, and HFU-2) of Bentiu Formation which comprises 95% of the flow capacity of the sequence. The average reservoir parameters of the studied sequence, including shale volume, effective porosity and hydrocarbon saturation, equal to 31.6, 16.2 and 39.5%, respectively with 29.5 m as a total net-pay thickness.Petrographically, the relatively low contribution of the Abu Gabra Formation is due to its authigenic mineral content, compaction, and cementation.

Exploring sub-basalt reservoirs using object-oriented imaging: A case study from Kutch–Saurashtra area, India

The hydrocarbon strike has been reported above and below basalt (Mesozoic sequences) in shallow water of Kutch–Saurashtra basin of Indian west coast. The evaluation of entrapment conditions within Mesozoic (below basalt) is extremely problematic because of poor quality images, of available data which are not amenable for subsurface mapping. The precise sub-basalt imaging in Kutch–Saurashtra basin is crucial for successful exploration activities in Mesozoic. The challenges for imaging the streamer data are two folds: first, poor data quality, due to poor signal penetration through basalt section and second, masking of signals with multiples and converted waves (PSPP and PSSP). Modelling using Norsar software, reveals that PSSP waves (noise), generate from an offset of about 3000 m from basalt top. We followed a new imaging strategy for achieving good sub-basalt images by proper multiple attenuation, elimination of converted waves, and adequate noise cleaning in different domains with correct estimation of velocity and signal boosting, below basalt. The new images clearly exhibit the sub-basalt horizons like Base of Basalt, Bhuj Formation and Mundra Formation, etc., which are amenable for mapping and pre-stack inversion, a powerful tool for reservoir characterization. The acoustic impedance of gas pay, drastically drops to 8000 unit from background value or 14000 units, delineated lateral extension of pay sand in present study. The new imaging exhibits presence of Graben, half Graben and anticlinal structures formed during Mesozoic and some reverse faults which are key components to unravel the basin tectonics and to aid derive Mesozoic petroleum system.

Predictive modeling of thermogenic methane hydrate formation and geobody distribution – Results from numerical simulations

Reservoir characterization of thermogenic gas hydrates have so far been limited to seismic mapping, well log interpretation, and lab scale experiments, with numerical modeling mostly focusing on gas production from hydrates. What is unknown however is the hydrate saturation at the sub-seismic and interwell scales. This study uses numerical simulations for predictive modeling of hydrate formation and geobody distribution using TOUGH + Hydrate. Results indicate that the flow of gas is buoyancy and advection dominated, and affects hydrate formation rate and saturation distribution. Geological controls such as fault angles, stratigraphic thickness, permeabilities and permeability anisotropies and contrasts with adjacent formations significantly impact distribution of hydrate saturation, and geobody shape. Hydrates form in both high and low porosity rocks. While full-scale reservoir modeling is contingent upon the availability of detailed reservoir and fluid data, this study underscores the importance of using numerical modeling tools for quantitative predictive modeling and reservoir characterization of hydrate reservoirs for better resource estimation, well-placement decisions, reservoir management and production planning.

3D S-wave velocity imaging of Reykjanes Peninsula high-enthalpy geothermal fields with ambient-noise tomography

Tomographic imaging based on ambient seismic noise measurements has shown to be a powerful tool, especially in areas like Iceland, where the microseism illumination is excellent. In this paper, we produce a 3D S-wave tomographic image over the western Reykjanes Peninsula high-enthalpy geothermal fields and evaluate the reliability of the tomographic results for different resolutions through simulated and real data. We use 30 broadband stations operating for approximately one-and-a-half year and apply ambient noise seismic interferometry for each station-pair. This results in empirical Green's functions in which especially the ballistic surface waves (BSW) are well resolved. The retrieved BSW exhibit a high signal-to-noise ratio between 0.1 and 0.5 Hz, and the beamforming analysis indicates an apparent surface-wave velocity of 3 km/s over a broad azimuthal range. For the tomographic inversion, we invert the estimated phase velocities between all station pairs to frequency-dependent phase velocity maps in four different resolutions (1, 2, 3, and 4 km) using a Tikhonov regularisation. With the estimated regularisation parameter per frequency per resolution, we invert simulated data for checkerboard sensitivity tests per frequency for different combinations of velocity anomaly sizes and resolutions.Finally, after the inversion to depth, we detect S-wave velocity anomalies with variations between −15% and 15% with reference to an estimated average velocity using 1 km and 3 km of lateral resolutions and 1 km of vertical resolution. This study shows the potential of ambient noise tomography as complementary seismological tool for reservoir characterization.

Petrophysical Evaluation of a Severely Heterogeneous Carbonate Reservoir; Electrical Image Logs Usage in Porosity Estimation

Image logs have higher resolution than conventional logs and it makes them powerful tools for detailed reservoir characterization and modeling. Hence, thin beds, which are not detectable using conventional logs, can be characterized by image log data. The present study focuses on the Permian-Triassic carbonate reservoirs of Dalan and Kangan formations in one of the gas fields in southern Iran. In this study, the reservoir porosity was estimated using Fullbore Formation Microimager (FMI) image log. Then, the results were compared and validated with the core data. Porosity was estimated as 2-dimentional image by rescaling the FMI image log with Micro-Spherical Focused Log (MSFL). The image log-derived porosity was then compared with conventional logs-derived and core porosities. The image log-derived porosity is in good agreement with the core data. In this paper, a procedure was introduced which can be used to recognize very narrow pay layers (thickness in centimeters). This work is very important for identifying the proper perforation intervals in heterogeneous reservoirs.

Bayesian framework for elastic full-waveform inversion with facies information

Conventional reservoir-characterization techniques utilize amplitude-variation-with-offset (AVO) analysis to invert for the elastic parameters or directly for the physical properties of reservoirs. However, the quality of AVO inversion is degraded by errors in the velocity model, inaccurate amplitudes, and structural complexity. Whereas full-waveform inversion (FWI) potentially represents a much more powerful tool for reservoir characterization. FWI strongly relies on the accuracy of the initial model and suffers from parameters trade-offs. Here, we use a probabilistic Bayesian framework to supplement data fitting with rock-physics constraints based on geologic facies obtained from borehole information (well logs). The advantages of the facies-based FWI are demonstrated on a structurally complex isotropic elastic model and on a 3D layered VTI (transversely isotropic with a vertical symmetry axis) medium. In particular, the tests show that our algorithm can operate without ultra-low-frequency data required by conventional FWI and can reduce crosstalk between the medium parameters.

On the application of the Eshelby-Cheng effective model in a porous cracked medium with background anisotropy: An experimental approach

Understanding the effect of cracks in elastic media is important for hydrocarbon recovery, especially in nonconventional reservoirs. Consequently, due to the presence of oriented cracks on these types of reservoirs, an anisotropic behavior can be induced. In terms of seismic or ultrasonic velocities, this means that elastic waves propagating on regions with oriented cracks have their velocities varying with the propagation and polarization directions. Thus, the analysis of the seismic wave velocities in a cracked medium can be used as a tool for reservoir characterization. For this reason, there is a variety of mathematical models to describe transversely isotropic cracked medium as well as the design of several experiments to test these models. We have experimentally analyzed the theoretical predictions of Eshelby-Cheng’s first-order model. For this proposal, we measured P- and S-wave ultrasonic velocities in 17 anisotropic samples. All samples indicate weak background anisotropy due to layering deposition; i.e., they are vertical transversely isotropic (VTI) media. Sixteen synthetic anisotropic samples with different crack densities and aspect ratios were simulated by penny-shaped void inclusions in a homogeneous porous matrix made with cement and sand. An uncracked sample, with weak VTI anisotropy, was constructed for reference. The crack densities and aspect ratios ranged from 0 to 0.102 and from 0 to 0.52, respectively. All measurements were performed in a dry condition. From the experimental and theoretical velocities, we calculated the Thomsen’s parameters and correlated them with the crack density. An efficient flowchart was developed to make feasible and clear the inversion of the output Eshelby-Cheng’s effective elastic coefficients in effective velocities. Our results suggest that the anisotropy increases with crack density. In general, we noted that the best fit between the Eshelby-Cheng’s model and the experimental results occurs when the crack density and aspect ratio were lower than 0.1 and 0.32, respectively, and it is largely dependent on the type of crack porosity’s equation used in the inversion of effective stiffness coefficients in the elastic effective velocities.

Cognitive seismic data modelling based successive differential evolution algorithm for effective exploration of oil-gas reservoirs

A cognitive modelling based new inversion method, the successive differential evolution (DE-S) algorithm, is proposed to estimate the Q factor and velocity from the zero-offset vertical seismic profile (VSP) record for oil-gas reservoir exploration. The DE algorithm seeks optimal solutions by simulating the natural species evolution processes and makes the individuals become optimal. This algorithm is suitable for the high-dimensional nonseparable model space where the inversion leads to recognition and prediction of hydrocarbon reservoirs. The viscoelastic medium is split into layers whose thicknesses equal to the space between two successive VSP geophones, and the estimated parameters of each layer span the related subspace. All estimated parameters span to a high dimensional nonseparable model space. We develop bottom-up workflow, in which the Q factor and the velocity are estimated using the DE algorithm layer by layer. In order to improve the inversion precision, the crossover strategy is discarded and we derive the weighted mutation strategy. Additionally, two kinds of stopping criteria for effective iteration are proposed to speed up the computation. The new method has fast speed, good convergence and is no longer dependent on the initial values of model parameters. Experimental results on both synthetic and real zero-offset VSP data indicate that this method is noise robust and has great potential to derive reliable seismic attenuation and velocity, which is an important diagnostic tool for reservoir characterization.

An improved peak frequency shift method for Q estimation based on generalized seismic wavelet function

As a powerful tool for hydrocarbon detection and reservoir characterization, the quality factor, Q, provides useful information in seismic data processing and interpretation. In this paper, we propose a novel method for Q estimation. The generalized seismic wavelet (GSW) function was introduced to fit the amplitude spectrum of seismic waveforms with two parameters: fractional value and reference frequency. Then we derive an analytical relation between the GSW function and the Q factor of the medium. When a seismic wave propagates through a viscoelastic medium, the GSW function can be employed to fit the amplitude spectrum of the source and attenuated wavelets, then the fractional values and reference frequencies can be evaluated numerically from the discrete Fourier spectrum. After calculating the peak frequency based on the obtained fractional value and reference frequency, the relationship between the GSW function and the Q factor can be built by the conventional peak frequency shift method. Synthetic tests indicate that our method can achieve higher accuracy and be more robust to random noise compared with existing methods. Furthermore, the proposed method is applicable to different types of source wavelet. Field data application also demonstrates the effectiveness of our method in seismic attenuation and the potential in the reservoir characteristic.