A hybrid machine learning optimization algorithm for multivariable pore pressure prediction

Pore pressure is essential data in drilling design,and its accurate prediction is necessary to ensure drilling safety and improve drilling efficiency.Traditional methods for predicting pore pressure are limited when forming particular structures and lithology.In this paper,a machine learning algorithm and effective stress theorem are used to establish the transformation model between rock physical parameters and pore pressure.This study collects data from three wells.Well 1 had 881 data sets for model training,and Wells 2 and 3 had 538 and 464 data sets for model testing.In this paper,support vector machine(SVM),random forest(RF),extreme gradient boosting(XGB),and multilayer perceptron(MLP)are selected as the machine learning algorithms for pore pressure modeling.In addition,this paper uses the grey wolf optimization(GWO)algorithm,particle swarm optimization(PSO)algorithm,sparrow search algorithm(SSA),and bat algorithm(BA)to establish a hybrid machine learning optimization algorithm,and proposes an improved grey wolf optimization(IGWO)algorithm.The IGWO-MLP model obtained the minimum root mean square error(RMSE)by using the 5-fold cross-validation method for the training data.For the pore pressure data in Well 2 and Well 3,the coefficients of determination(R^(2))of SVM,RF,XGB,and MLP are 0.9930 and 0.9446,0.9943 and 0.9472,0.9945 and 0.9488,0.9949 and 0.9574.MLP achieves optimal performance on both training and test data,and the MLP model shows a high degree of generalization.It indicates that the IGWO-MLP is an excellent predictor of pore pressure and can be used to predict pore pressure.

Effects of confining pressure and pore pressure on multipole borehole acoustic field in fluid-saturated porous media

In-situ stress is a common stress in the exploration and development of oil reservoirs. Therefore, it is of great significance to study the propagation characteristics of borehole acoustic waves in fluid-saturated porous media under stress.Based on the acoustoelastic theory of fluid-saturated porous media, the field equation of fluid-saturated porous media under the conditions of confining pressure and pore pressure and the acoustic field formula of multipole source excitation in open hole are given. The influences of pore pressure and confining pressure on guided waves of multipole borehole acoustic field in fluid-saturated porous media are investigated. The numerical results show that the phase velocity and excitation intensity of guided wave increase significantly under the confining pressure. For a given confining pressure, the phase velocity of the guided wave decreases with pore pressure increasing. The excitation intensity of guided wave increases at low frequency and then decreases at high frequency with pore pressure increasing, except for that of Stoneley wave which decreases in the whole frequency range. These results will help us get an insight into the influences of confining pressure and pore pressure on the acoustic field of multipole source in borehole around fluid-saturated porous media.

Rock physics model for velocity–pressure relations and its application to shale pore pressure estimation

Acoustic wave velocity has been commonly utilized to predict subsurface geopressure using empirical relations.Acoustic wave velocity is, however, affected by many factors. To estimate pore pressure accurately, we here propose to use elastic rock physics models to understand and analyze quantitatively the various contributions from these different factors affecting wave velocity. We report a closed-form relationship between the frame flexibility factor(γ) in a rock physics model and differential pressure, which presents the major control of pressure on elastic properties such as bulk modulus and compressional wave velocity. For a gas-bearing shale with abundant micro-cracks and fractures, its bulk modulus is much lower at abnormally high pore pressure(high γ values) where thin cracks and flat pores are open than that at normal hydrostatic pressure(low γ values) where pores are more rounded on average. The developed relations between bulk modulus and differential pressure have been successfully applied to the Upper Ordovician Wufeng and Lower Silurian Longmaxi formations in the Dingshan area of the Sichuan Basin to map the three-dimensional spatial distribution of pore pressure in the shale, integrating core, log and seismic data. The estimated results agree well with field measurements. Pressure coefficient is positively correlated to gas content. The relations and methods reported here could be useful for hydrocarbon exploration, production, and drilling safety in both unconventional and conventional fields.

Influence of Hydrodynamic Pore Pressure Damage on the Performance of Hot-Mixed Renewable Asphalt Mixture

For evaluating the water stability of hot-mixed renewable asphalt mixture(HRM),the traditional methods are all tested under still water conditions.Except for damage in still water conditions,the hydrodynamic pore pressure generated by the tire driving on the surface water has a great impact.Thus,the RAP contents of the HRMs were designed at 0%,30%,45%and 60%with AC-25 gradation.Then,the self-designed evaluation methods of water stability and dynamic modulus were studied.Finally,the mechanism of the influence of hydrodynamic pore pressure damage on HRMs was studied.The results show that the water stability of HRM containing 30%RAP is equivalent to that of 45%RAP,and the water stability of HRM containing 60%RAP decreases significantly.The Contabro test after MIST treatment can be used as an evaluation method for hydrodynamic pore pressure damage on HRM.Low-speed,heavy-load traffic and larger RAP content have greater damage to the mixture after hydrodynamic pore pressure damage.The performance differences between the aged bitumen and pure bitumen,as well as the aged minerals and new minerals,are continuing to be enlarged in hydrodynamic pore pressure conditions,finally affecting the water stability and dynamic modulus of the HRMs.

Pore pressure prediction in offshore Niger delta using data-driven approach: Implications on drilling and reservoir quality

Despite exploration and production success in Niger Delta,several failed wells have been encountered due to overpressures.Hence,it is very essential to understand the spatial distribution of pore pressure and the generating mechanisms in order to mitigate the pitfalls that might arise during drilling.This research provides estimates of pore pressure along three offshore wells using the Eaton's transit time method,multi-layer perceptron artificial neural network(MLP-ANN)and random forest regression(RFR)algorithms.Our results show that there are three pressure magnitude regimes:normal pressure zone(hydrostatic pressure),transition pressure zone(slightly above hydrostatic pressure),and over pressured zone(significantly above hydrostatic pressure).The top of the geopressured zone(2873 mbRT or 9425.853 ft)averagely marks the onset of overpressurization with the excess pore pressure above hydrostatic pressure(P∗)varying averagely along the three wells between 1.06−24.75 MPa.The results from the three methods are self-consistent with strong correlation between the Eaton's method and the two machine learning models.The models have high accuracy of about>97%,low mean absolute percentage error(MAPE<3%)and coefficient of determination(R2>0.98).Our results have also shown that the principal generating mechanisms responsible for high pore pressure in the offshore Niger Delta are disequilibrium compaction,unloading(fluid expansion)and shale diagenesis.

Anisotropic Rock Poroelasticity Evolution in Ultra-low Permeability Sandstones under Pore Pressure,Confining Pressure,and Temperature:Experiments with Biot's Coefficient

This study aimed to show anisotropic poroelasticity evolution in ultra-low permeability reservoirs under pore pressure,confining pressure,and temperature.Several groups of experiments examining Biot's coefficient under different conditions were carried out.Results showed that Biot's coefficient decreased with increased pore pressure,and the variation trend is linear,but the decreasing rate is variable between materials.Biot's coefficient increased with increased confining pressure;the variation trend is linear,but the increasing rate varies by material as well.Generally,Biot's coefficient remains stable with increased temperature.Lithology,clay mineral content,particle arrangement,and pore arrangement showed impacts on Biot's coefficient.For strong hydrophilic clay minerals,expansion in water could result in a strong surface adsorption reaction,which could result in an increased fluid bulk modulus and higher Biot's coefficient.For skeleton minerals with strong lipophilicity,such as quartz and feldspar,increased oil saturation will also result in an adsorption reaction,leading to increased fluid bulk modulus and a higher Biot's coefficient.The study's conclusions provide evidence of poroelasticity evolution of ultra-low permeability and help the enhancing oil recovery(EOR)process.

An improved apparent permeability model considering full pore pressure range,variable intrinsic permeability and slippage coefficient

Although the slippage effect has been extensively studied,most of the previous studies focused on the impact of the slippage effect on apparent permeability within a low pore pressure range,resulting in the inability of matching the evolution of permeability in the remaining pressure range.In this paper,a new apparent permeability model that reveals the evolution of permeability under the combined action of effective stress and slippage in the full pore pressure range was proposed.In this model,both intrinsic permeability and slippage coefficient are stress dependent.Three experimental tests with pore pressure lower than 2 MPa and a test with pore pressure at about 10 MPa using cores from the same origin under constant confining stress and constant effective stress are conducted.By comparing experimental data and another apparent permeability model,we proved the fidelity of our newly developed model.Furthermore,the contribution factor of the slippage effect Rslip is used to determine the low pore pressure limit with significant slippage effect.Our results show that both narrow initial pore size and high effective stress increase the critical pore pressure.Finally,the evolutions of the slippage coefficient and the intrinsic permeability under different boundary conditions were analyzed.

Machine learning and data-driven prediction of pore pressure from geophysical logs:A case study for the Mangahewa gas field,New Zealand

Pore pressure is an essential parameter for establishing reservoir conditions,geological interpretation and drilling programs.Pore pressure prediction depends on information from various geophysical logs,seismic,and direct down-hole pressure measurements.However,a level of uncertainty accompanies the prediction of pore pressure because insufficient information is usually recorded in many wells.Applying machine learning(ML)algorithms can decrease the level of uncertainty of pore pressure prediction uncertainty in cases where available information is limited.In this research,several ML techniques are applied to predict pore pressure through the over-pressured Eocene reservoir section penetrated by four wells in the Mangahewa gas field,New Zealand.Their predictions substantially outperform,in terms of prediction performance,those generated using a multiple linear regression(MLR)model.The geophysical logs used as input variables are sonic,temperature and density logs,and some direct pore pressure measurements were available at the reservoir level to calibrate the predictions.A total of 25,935 data records involving six well-log input variables were evaluated across the four wells.All ML methods achieved credible levels of pore pressure prediction performance.The most accurate models for predicting pore pressure in individual wells on a supervised basis are decision tree(DT),adaboost(ADA),random forest(RF)and transparent open box(TOB).The DT achieved root mean square error(RMSE)ranging from 0.25 psi to 14.71 psi for the four wells.The trained models were less accurate when deployed on a semi-supervised basis to predict pore pressure in the other wellbores.For two wells(Mangahewa-03 and Mangahewa-06),semi-supervised prediction achieved acceptable prediction performance of RMSE of 130—140 psi;while for the other wells,semi-supervised prediction performance was reduced to RMSE>300 psi.The results suggest that these models can be used to predict pore pressure in nearby locations,i.e.similar geology at corresponding depths within a field,but they become less reliable as the step-out distance increases and geological conditions change significantly.In comparison to other approaches to predict pore pressures,this study has identified that application of several ML algorithms involving a large number of data records can lead to more accurate prediction results.

Experimental investigation on the wave-induced pore pressure around shallowly embedded pipelines

A series of regular wave experiments have been done in a large-scale wave flume to investigate the wave-induced pore pressure around the submarine shallowly embedded pipelines. The model pipelines are buried in three kinds of soils, including gravel, sand and silt with different burial depth. The input waves change with height and period. The results show that the amplitudes of wave-induced pore pressure increase as the wave period increase, and decay from the surface to the bottom of seabed. Higher pore pressures are recorded at the pipeline top and the lower pore pressures at the bottom, especially in the sand seabed. The normalized pressure around pipeline decreases as the relative water depth, burial depth or scattering parameters increase. For the silt seabed, the wavelet transform has been successfully used to analyze the signals of wave - induced pore pressure, and the oscillatory and residual pore pressure can be extracted by wavelet analysis. Higher oscillatory pressures are recorded at the bottom and the lower pressures at the top of the pipeline. However, higher residual pressures are recorded at the top and the lower pressures at the bottom of the pipeline.

Tight gas production model considering TPG as a function of pore pressure,permeability and water saturation

Threshold pressure gradient has great importance in efficient tight gas field development as well as for research and laboratory experiments.This experimental study is carried out to investigate the threshold pressure gradient in detail.Experiments are carried out with and without back pressure so that the effect of pore pressure on threshold pressure gradient may be observed.The trend of increasing or decreasing the threshold pressure gradient is totally opposite in the cases of considering and not considering the pore pressure.The results demonstrate that the pore pressure of tight gas reservoirs has great influence on threshold pressure gradient.The effects of other parameters like permeability and water saturation,in the presence of pore pressure,on threshold pressure gradient are also examined which show that the threshold pressure gradient increases with either a decrease in permeability or an increase in water saturation.Two new correlations of threshold pressure gradient on the basis of pore pressure and permeability,and pore pressure and water saturation,are also introduced.Based on these equations,new models for tight gas production are proposed.The gas slip correction factor is also considered during derivation of this proposed tight gas production models.Inflow performance relationship curves based on these proposed models show that production rates and absolute open flow potential are always be overestimated while ignoring the threshold pressure gradients.

Soil pressure and pore pressure for seismic design of tunnels revisited: considering water-saturated, poroelastic half-space

This paper describes a systematic study on the fundamental features of seismic soil pressure on underground tunnels, in terms of its magnitude and distribution, and further identifi es the dominant factors that signifi cantly infl uence the seismic soil pressure. A tunnel embedded in water-saturated poroelastic half-space is considered, with a large variety of model and excitation parameters. The primary features of both the total soil pressure and the pore pressure are investigated. Taking a circular tunnel as an example, the results are presented using a fi nite element-indirect boundary element(FE-IBE) method, which can account for dynamic soil-tunnel interaction and solid frame-pore water coupling. The effects of tunnel stiffness, tunnel buried depth and input motions on the seismic soil pressure and pore pressure are also examined. It is shown that the most crucial factors that dominate the magnitude and distribution of the soil pressure are the tunnel stiffness and dynamic soil-tunnel interaction. Moreover, the solid frame-pore water coupling has a prominent infl uence on the magnitude of the pore pressure. The fi ndings are benefi cial to obtain insight into the seismic soil pressure on underground tunnels, thus facilitating more accurate estimation of the seismic soil pressure.

Influential factors of loess liquefaction and pore pressure development

The liquefaction of loess under dynamic loading is studied experimentally with a dynamic triaxial test system. The effects of over-consolidation ratio (OCR), saturation degree and the frequency of dynamic loading upon loess liquefaction are investigated. The development of pore pressure within loess samples is also discussed. Based on the experimental results, the empirical relationship between pore pressure ratio and loading cycle number ratio is established for normal consolidated saturated loess.

In Situ Observation of Silt Seabed Pore Pressure Response to Waves in the Subaqueous Yellow River Delta

The in situ pore pressure response of silt under wave action is a complex process.However,this process has not been well studied because of limited field observation techniques.The dynamic response process is closely related to engineering geological hazards;thus,this process must be urgently explored.A long-term in situ observational study of the silt sediment pore water pressure response process under wave action was conducted in the subaqueous Yellow River Delta.The response characteristics of pore water pressure are affected by tidal level and wave height.Tidal level affects the overall trend of the pore water pressure response,while wave height influences the amplitude of the pore water pressure response.This study revealed a significant lag effect in the pore pressure response.The transient pore pressure in the seabed did not respond immediately to the wave-induced pressure stress on the seabed surface.This phenomenon may be attributed to the change in soil permeability.The maximum response depth was approximately 0.5 m with a 2 m wave height.A concept model of silt soil pore pressure response under different types of wave action was developed.The accumulation rate of the pore pressure is less than the dissipation rate;thus,the developed model highlights the oscillation pore pres-sure response mechanism.The highlighted response process is of considerable importance to transient liquefaction and the startup process of pore pressure response.

Capture the variation of the pore pressure with different geological age from seismic inversion study in the Jaisalmer sub-basin,India

Geoscientific evidence shows that various parameters such as compaction,buoyancy effect,hydrocarbon maturation,gas effect and tectonic activities control the pore pressure of sub-surface geology.Spatially controlled geoscientific data in the tectonically active areas is significantly useful for robust estimation of pre-drill pore pressure.The reservoir which is tectonically complex and pore pressure is changing frequently that circumference motivated us to conduct this study.The changes in pore pressure have been captured from the fine-scale to the broad scale in the Jaisalmer sub-basin.Pore pressure variation has been distinctly observed in pre-and post-Jurassic age based on the current study.Post-stack seismic inversion study was conducted to capturing the variation of pore pressure.Analysis of low-frequency spectrum and integrated interval velocity model provided a detailed feature of pore pressure in each compartment of the study area.Pore pressure estimated from well log data was correlated with seismic inversion based result.Based on the current study one well has been proposed where pore pressure was estimated and two distinguished trends are identified in the study zone.The approaches of the current study were analysed thoroughly and it will be highly useful in complex reservoir condition where pore pressure varies frequently.

Integrated Approach to Pore Pressure and Fracture Pressure Prediction Using Well Logs: Case Study of Onshore Niger-Delta Sedimentary Basin

This study investigated the cause of identified zones of overpressure in some selected wells in a field in the Niger Delta sedimentary basin. Two models were used each for predicting pore pressure and the corresponding fracture pressure using well log and drilling data. Shale lithology in Niger Delta is massive and characterized by high pore pressure;hence shale compaction theory is utilized in this study. The petrophysical data were evaluated using Ikon’s Science Rokdoc software. The two major pore pressure prediction techniques employed are the Eaton’s and Bowers’ models while the Eaton’s fracture pressure model and the Hubbert and Willis fracture pressure prediction models were utilized for fracture prediction. The density and sonic logs were used respectively to generate the shale trend and the shale normal compaction trend used for the prediction. The wells studied showed disequilibrium compaction of sediment to be the major mechanism that gave rise to overpressure in the Niger Delta. Clay diagenesis and fluid expansion were also observed as the secondary overpressure generation mechanism in well X-1. This secondary overpressure mechanism was observed to start approximately at depths of 10,000 ft (TVD). The top of overpressure and the pressure range in the wells studied varied from 6000 to 11,017 ft (TVD) and 1796.70 to 5297.00 psi respectively. The Eaton’s model under-predicts pore pressure at the depth interval where unloading mechanism is witnessed. Since the study revealed presence of secondary overpressure generation mechanism, Bowers model was observed to be the most reliable pore pressure prediction model in the area.

Analysis of wellbore stability by pore pressure prediction using seismic velocity

Borehole problems result in the wastage of huge expenditures in petroleum industry.One of the major challenges is to keep the borehole intact at a particular location and prevent it from falling in reactive shale in high-or low-pressure zones.To convert seismic velocity to pore pressure,the modified Eaton's equation is widely used.A guideline was prepared using both stochastic and non-uniform parameter distributions.Pore pressure and fracture pressure were calculated using a modified version of Eaton's and Mathew and Kelly's methods.To validate the results,geomechanical models were developed based on good correlation.Different regions in the eastern state of India at Tripura were taken into consideration and pore pressure was estimated for the regions of Kathalchari and Ambassa by plotting pressures.The actual pore pressure predicted in Tripura was calculated using seis P and seis P3,the indigenous software which is a modified version of Eaton's method and Mathew and Kelly's method,and the pore pressure from our method matches the calculated Repeat Formation Test(RFT)data from wells.

New Pore Pressure Evaluation Techniques for LAGIA-8 Well, Sinai, Egypt as a Case Study

Drilling into a geopressured zone will generally cause a change in a number of basic formation/ drilling relationships. This change is usually seen as a reversal of a gradual depth related trend in a lithologically uniform formation. Of all the geophysical methods, the reflection seismic method is essentially the only technique used to predict pore pressures. The seismic method detects changes of interval velocity with depth from velocity analysis of the seismic data. These changes are in turn related to lithology, pore fluid type, rock fracturing and pressure changes within a stratigraphic column. When the factors affecting the velocity are understood for a given area, a successful pressure prediction can be made. For clastic environments such as the Tertiary section of the Gulf of Mexico or the Niger delta, the interval velocity of the rocks increases with depth because of compaction. In these areas, deviations from normal compaction trends are related to abnormally high pore pressures. The adapted methods provide a much easier way to handle normal compaction trend lines. In addition to well log methods, pressure detection can be obtained via drilling parameters by applying Eaton’s DXC methods. Seismic velocities have long been used to estimate pore pressure, indeed both these quantities are influenced by variations in rock properties such as porosity, density, effective stress and so on, and high pore pressure zones are often associated with low seismic velocities. Pressure prediction from seismic data is based on fundamentals of rock physics and seismic attribute analysis. This paper hence tries to assess the use of seismic waves as a viable means to calculate pore pressure, especially in areas where no prior drilling history can be found. Then we applied these methods on LAGIA-8 well, Sinai, Egypt as a case study. Pore pressure prediction from Seismic is a very essential tool to predict pore pressure before drilling operation. This could prevent the well problem as well blowout and to prevent formation damage, especially in areas where no prior drilling history can be found.

New Pore Pressure Evaluation Techniques for LAGIA-8 Well, Sinai, Egypt as a Case Study

Drilling into a geopressured zone will generally cause a change in a number of basic formation/ drilling relationships. This change is usually seen as a reversal of a gradual depth related trend in a lithologically uniform formation. Of all the geophysical methods, the reflection seismic method is essentially the only technique used to predict pore pressures. The seismic method detects changes of interval velocity with depth from velocity analysis of the seismic data. These changes are in turn related to lithology, pore fluid type, rock fracturing and pressure changes within a stratigraphic column. When the factors affecting the velocity are understood for a given area, a successful pressure prediction can be made. For clastic environments such as the Tertiary section of the Gulf of Mexico or the Niger delta, the interval velocity of the rocks increases with depth because of compaction. In these areas, deviations from normal compaction trends are related to abnormally high pore pressures. The adapted methods provide a much easier way to handle normal compaction trend lines. In addition to well log methods, pressure detection can be obtained via drilling parameters by applying Eaton’s DXC methods. Seismic velocities have long been used to estimate pore pressure, indeed both these quantities are influenced by variations in rock properties such as porosity, density, effective stress and so on, and high pore pressure zones are often associated with low seismic velocities. Pressure prediction from seismic data is based on fundamentals of rock physics and seismic attribute analysis. This paper hence tries to assess the use of seismic waves as a viable means to calculate pore pressure, especially in areas where no prior drilling history can be found. Then we applied these methods on LAGIA-8 well, Sinai, Egypt as a case study. Pore pressure prediction from Seismic is a very essential tool to predict pore pressure before drilling operation. This could prevent the well problem as well blowout and to prevent formation damage, especially in areas where no prior drilling history can be found.

Pore Pressure Accumulation of Anisotropically Consolidated Soft Clay Subjected to Complex Loads Under Different Stress Paths

Owing to different influence factors of foundation soil,the initial stress state of the soil under various working conditions is complex.To simulate this situation,in this paper,a series of tests on undisturbed soft clay under pure principal stress axis rotation were carried out by using the hollow cylinder apparatus(HCA).The influence of initial consolidation angle ζ(the angle between the vertical direction and direction of the applied load in consolidation)and intermediate principal stress coefficient b on pore water pressure accumulation of undisturbed soft clay were mainly studied.The test results show that,during pure principal stress axis rotation,the pore water pressure accumulation of the undisturbed soft clay fluctuates and increases with the rotation of the major principal stress;the values of major principal stress anglesα,corresponding to the peak value of the pore water pressure in a certain cycle,are different with different initial consolidation angles;the pore water pressure accumulation of soft clay is greatly affected by the intermediate principal stress coefficient b.With the fixed initial consolidation angle ζ,the variation trend of the maximum pore water pressure for each cycle is appropriately the same with different b values.With the increase of cycles,the difference value of pore water pressure between b=0 and b=1 in each cycle increases gradually with different initial consolidation angles ζ.While with different initial consolidation anglesζ,the increase of the pore water pressure when b increases from 0 to 0.5 is different with that when b increases from 0.5 to 1;the variation of maximum pore water pressure withζis significantly affected by the value of b;the value of maximum pore water pressure increases with the cycle number increases under all test conditions,but the growth rate decreases gradually.And the variation of maximum pore water pressure with the cycle number N is obviously influenced by both ζ and b.

An adaptive physics-informed deep learning method for pore pressure prediction using seismic data

Accurate prediction of formation pore pressure is essential to predict fluid flow and manage hydrocarbon production in petroleum engineering.Recent deep learning technique has been receiving more interest due to the great potential to deal with pore pressure prediction.However,most of the traditional deep learning models are less efficient to address generalization problems.To fill this technical gap,in this work,we developed a new adaptive physics-informed deep learning model with high generalization capability to predict pore pressure values directly from seismic data.Specifically,the new model,named CGP-NN,consists of a novel parametric features extraction approach(1DCPP),a stacked multilayer gated recurrent model(multilayer GRU),and an adaptive physics-informed loss function.Through machine training,the developed model can automatically select the optimal physical model to constrain the results for each pore pressure prediction.The CGP-NN model has the best generalization when the physicsrelated metricλ=0.5.A hybrid approach combining Eaton and Bowers methods is also proposed to build machine-learnable labels for solving the problem of few labels.To validate the developed model and methodology,a case study on a complex reservoir in Tarim Basin was further performed to demonstrate the high accuracy on the pore pressure prediction of new wells along with the strong generalization ability.The adaptive physics-informed deep learning approach presented here has potential application in the prediction of pore pressures coupled with multiple genesis mechanisms using seismic data.