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.

Water-induced physicochemical and pore changes in limestone for surrounding rock across pressure aquifers

Osmotic water alters the physicochemical properties and internal structures of limestone.This issue is particularly critical in tunnel construction across mountainous regions with aquifers,where pressurized groundwater can destabilize the limestone-based surrounding rock.Thus,systematic research into the physicochemical properties and pore structure changes in the limestone under pressurized water is essential.Additionally,it is essential to develop an interpretable mathematical model to accurately depict how pressurized osmotic water weakens limestone.In this research,a specialized device was designed to simulate the process of osmotic laminar flow within limestone.Then,four main tests were conducted:mass loss,acoustic emission(AE),mercury intrusion porosimetry(MIP),and fluorescence analysis.Experimental results gained from tests led to the development of a“Particle-pore throat-water film”model.Proposed model explains water-induced physicochemical and pore changes in limestone under osmotic pressure and reveals evolutionary mechanisms as pressure increases.Based on experimental results and model,we found that osmotic pressure not only alters limestone composition but also affects pore throats larger than 0.1μm.Furthermore,osmotic pressure expands pore throats,enhancing pore structure uniformity,interconnectivity,and permeability.These effects are observed at a threshold of 7.5 MPa,where cohesive forces within the mineral lattice are surpassed,leading to the breakdown of erosion-resistant layer and a significant increase in hydrochemical erosion.

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.

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.

Prediction of the Pore-Pressure Built-Up and Temperature of Fire-Loaded Concrete with Pix2Pix

Concrete subjected to fire loads is susceptible to explosive spalling, which can lead to the exposure of reinforcingsteel bars to the fire, substantially jeopardizing the structural safety and stability. The spalling of fire-loaded concreteis closely related to the evolution of pore pressure and temperature. Conventional analytical methods involve theresolution of complex, strongly coupled multifield equations, necessitating significant computational efforts. Torapidly and accurately obtain the distributions of pore-pressure and temperature, the Pix2Pix model is adoptedin this work, which is celebrated for its capabilities in image generation. The open-source dataset used hereinfeatures RGB images we generated using a sophisticated coupled model, while the grayscale images encapsulate the15 principal variables influencing spalling. After conducting a series of tests with different layers configurations,activation functions and loss functions, the Pix2Pix model suitable for assessing the spalling risk of fire-loadedconcrete has been meticulously designed and trained. The applicability and reliability of the Pix2Pix model inconcrete parameter prediction are verified by comparing its outcomes with those derived fromthe strong couplingTHC model. Notably, for the practical engineering applications, our findings indicate that utilizing monochromeimages as the initial target for analysis yields more dependable results. This work not only offers valuable insightsfor civil engineers specializing in concrete structures but also establishes a robust methodological approach forresearchers seeking to create similar predictive models.

A machine learning approach for the prediction of pore pressure using well log data of Hikurangi Tuaheni Zone of IODP Expedition 372,New Zealand

Pore pressure(PP)information plays an important role in analysing the geomechanical properties of the reservoir and hydrocarbon field development.PP prediction is an essential requirement to ensure safe drilling operations and it is a fundamental input for well design,and mud weight estimation for wellbore stability.However,the pore pressure trend prediction in complex geological provinces is challenging particularly at oceanic slope setting,where sedimentation rate is relatively high and PP can be driven by various complex geo-processes.To overcome these difficulties,an advanced machine learning(ML)tool is implemented in combination with empirical methods.The empirical method for PP prediction is comprised of data pre-processing and model establishment stage.Eaton's method and Porosity method have been used for PP calculation of the well U1517A located at Tuaheni Landslide Complex of Hikurangi Subduction zone of IODP expedition 372.Gamma-ray,sonic travel time,bulk density and sonic derived porosity are extracted from well log data for the theoretical framework construction.The normal compaction trend(NCT)curve analysis is used to check the optimum fitting of the low permeable zone data.The statistical analysis is done using the histogram analysis and Pearson correlation coefficient matrix with PP data series to identify potential input combinations for ML-based predictive model development.The dataset is prepared and divided into two parts:Training and Testing.The PP data and well log of borehole U1517A is pre-processed to scale in between[-1,+1]to fit into the input range of the non-linear activation/transfer function of the decision tree regression model.The Decision Tree Regression(DTR)algorithm is built and compared to the model performance to predict the PP and identify the overpressure zone in Hikurangi Tuaheni Zone of IODP Expedition 372.

Research on Multi-Wave Pore Pressure Prediction Method Based on Three Field Velocity Fusion

The optimization of velocity field is the core issue in reservoir seismic pressure prediction. For a long time, the seismic processing velocity analysis method has been used in the establishment of pressure prediction velocity field, which has a long research period and low resolution and restricts the accuracy of seismic pressure prediction;This paper proposed for the first time the use of machine learning algorithms, based on the feasibility analysis of wellbore logging pressure prediction, to integrate the CVI velocity inversion field, velocity sensitive post stack attribute field, and AVO P-wave and S-wave velocity reflectivity to obtain high-precision seismic P and S wave velocities. On this basis, high-resolution formation pore pressure and other parameters prediction based on multi waves is carried out. The pressure prediction accuracy is improved by more than 50% compared to the P-wave resolution of pore pressure prediction using only root mean square velocity. Practice has proven that the research method has certain reference significance for reservoir pore pressure prediction.

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.

Characterization of reservoir properties and pore structure based on micro-resistivity imaging logging: Porosity spectrum, permeability spectrum, and equivalent capillary pressure curve

According to the capillary theory,an equivalent capillary model of micro-resistivity imaging logging was built.On this basis,the theoretical models of porosity spectrum(Ф_(i)),permeability spectrum(K_(i))and equivalent capillary pressure curve(pe)were established to reflect the reservoir heterogeneity.To promote the application of the theoretical models,the Archie's equation was introduced to establish a general model for quantitatively characterizing bi,K,and pei.Compared with the existing models,it is shown that:(1)the existing porosity spectrum model is the same as the general equation of gi;(2)the Ki model can display the permeability spectrum as compared with Purcell's permeability model;(3)the per model is constructed on a theoretical basis and avoids the limitations of existing models that are built only based on the component of porosity spectrum,as compared with the empirical model of capillary pressure curve.The application in the Permian Maokou Formation of Well TsX in the Central Sichuan paleo-uplift shows that the Ф_(i),K_(i),and p_(ci) models can be effectively applied to the identification of reservoir types,calculation of reservoir properties and pore structure parameters,and evaluation of reservoir heterogeneity.

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.

Numerical simulation of dynamic pore pressure in asphalt pavement

For studying the driving role of dynamic pressure in water-induced damage of asphalt pavement, based on the fast Lagrangian finite difference method and Biot dynamic consolidation theory, fluid-solid coupling analysis of the pavement is conducted considering asphalt mixtures as porous media. Results reveal that the development and dissipation of the dynamic pore pressure are coinstantaneous and this makes both the positive and negative dynamic pore pressure and seepage force alternate with time. Repetitive hydrodynamic pumping and sucking during moisture damage is proved. The dynamic pore pressure increases with vehicle velocity. Effective stress and deflection of pavement decrease due to the dynamic pore water pressure. However, the emulsification and replacement of the asphalt membrane by water are accelerated. The maximum dynamic pore pressure occurs at the bottom of the surface course. So it is suggested that a drain course should be set up to change the draining condition from single-sided drain to a two-sided drain, and thus moisture damage can be effectively limited.

The Influence of Atmospheric Pressure on Air Content and Pore Structure of Air-entrained Concrete

To study the effect of atmospheric pressure on the properties of fresh and hardened airentrained concrete, three kinds of air entraining agents were used for preparing air-entrained concrete in the plateaus(Lhasa, 61 kPa) and the plains(Beijing, 101 kPa). Air content, slump, compressive strength and pore structure of the three air-entrained concretes were tested in these two places. It is found that the air content of concrete under low atmospheric pressure(LAP) is 4%-36% lower than that of concrete under normal atmospheric pressure(NAP), which explaines the decrease of slump for air-entrained concrete under LAP. Pore number of hardened concrete under LAP is reduced by 48%-69%. While, the proportion of big pores(pore diameter >1 200 μm) and air void spacing factor are increased by 1.5%-7.3% and 51%-92%, respectively. The deterioration of pore structure results in a 3%-9% reduction in the compressive strength of concrete. From the results we have obtained, it can be concluded that the increase of critical nucleation energy of air bubbles and the decrease of volumetric compressibility coefficient of air in the concrete are responsible for the variation of air content and pore structure of concrete under LAP.

Wave-induced pore water pressure in marine cohesive soils

Cyclic triaxial tests and numerical analyses were undertaken, in order to evaluate the wave-induced pore water pressure in seabed sediments in the Hangzhou Bay. The cyclic triaxial tests indicate that the rate of pore water pressure generation in cohesive soils decreases with time, and the development of the pore water pressure can be represented by a hyperbolic curve. Numerical analyses, taking into account the generation and dissipation of pore water pressure simultaneously, suggest that the pore water pressure buildup in cohesive soils may increase with time continuously until the pore water pressure ratio approaches to 1, or it may decrease after a certain time, which is controlled by drain conditions. These phenomena are different from those in sands. For waves with a retum period of 100 a in the Hangzhou Bay, if the wave duration is more than 60 h, then the pore water pressure ratio will be close to 1 and soil fabric failure will take place.

Pore-scale study of the pressure-sensitive effect of sandstone and its influence on multiphase flows

The pressure-sensitive effect on the pore structure of sandstone was investigated using X-ray computed micro-tomography and QEMSCAN quantitative mineral analysis. In a physical simulation study, we extracted the pore network model from digital cores at different confining pressures and evaluated the effect of pressure sensitivity on the multiphase displacement process. In both the pore network model and QEMSCAN scanning, the pore structure was observed to be damaged under a high confining pressure. Due to their different scales, the pores and throats exhibited inhomogeneous changes; further, the throats exhibited a significant variation compared to that exhibited by the pores. Meanwhile, the heterogeneity of the pore structure under the two aforementioned activities was aggravated by the elastic-plastic deformation of the pore structure.The pressure-sensitive effect increased the proportion of mineral particles, such as quartz(the main component of the core skeleton), and reduced the proportion of clay minerals. The clay minerals were originally attached to the pore walls or interspersed in the pores; however, as the pressure increased, the clay minerals accumulated in the pores resulting in blockage of the pores. While simulating the multiphase displacement process, increasing the confining pressure was observed to severely restrict the flowability of oil and water. This study promises to improve the efficiency of reservoir development in terms of oil and gas exploitation.

Pore pressure observation: pressure response of probe penetration and tides

Excess pore water pressure is an important parameter that can be used to analyze certain physical characteristics of sediment.In this paper,the excess pore water pressure of subseafloor sediment and its variation with tidal movement was measured following the installation of a wharf in Qingdao,China by using a fiber Bragg grating(FBG)piezometer.The results indicated that this FBG piezometer is effective in the field.The measured variation of excess pore water pressure after installation is largely explained by the dissipation of excess pore water pressure.The dissipation rate can be used to estimate the horizontal consolidation coefficient,which ranged from 1.3×10^–6 m^2/s to 8.1×10^–6 m^2/s.The measured values during tidal phases are associated with the variability of tidal pressure on the seafloor and can be used to estimate the compressibility and the permeability of the sediment during tidal movement.The volume compression coefficient estimated from tidal oscillation was approximately 2.0×10^–11 Pa^–1,which was consistent with the data from the laboratory test.The findings of this paper can provide useful information for in situ investigations of subseafloor sediment.

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.

Influences of material dilatancy and pore water pressure on stability factor of shallow tunnels

Explicit finite difference code was used to calculate the stability factors of shallow tunnels without internal support in limit state. The proposed method was formulated within the nonassociative plasticity. For the shallow tunnels in soft clay, without considering the influences of pore water pressure and dilatancy, numerical results were compared with the previously published solutions. From the comparisons, it is found that the present solutions agree well with the previous solutions. The accuracy of the strength reduction technique was demonstrated through the comparisons. The influence of the pore water pressure was discussed. For the shallow tunnels in dilatant cohesive-frictional soils, the dilatant analysis was carried out.

Initial excess pore water pressures induced by tunnelling in soft ground

Tunnelling-induced long-term consolidation settlement attracts a great interest of engineering practice. The distribution and magnitude of tunnelling-induced initial excess pore water pressure have significant effects on the long-term consolidation settlement. A simple and reliable method for predicting the tunnel-induced initial excess pore water pressure calculation in soft clay is proposed. This method is based on the theory of elasticity and SKEMPTON's excess pore water pressure theory. Compared with the previously published field measurements and the finite-element modelling results, it is found that the suggested initial excess pore water pressure theory is in a good agreement with the measurements and the FE results. A series of parametric analyses are also carried out to investigate the influences of different factors on the distribution and magnitude of the initial excess pore water pressure in soft ground.

Sediment Compaction and Pore Pressure Prediction in Deepwater Basin of the South China Sea: Estimation from ODP and IODP Drilling Well Data

Overpressure in deepwater basins not only causes serious soft sediment deformation, but also significantly affects the safety of drilling operations. Therefore, prediction of overpressure in sediments has become an important task in deepwater oil exploration and development. In this study, we analyze the drilling data from ODP Leg 184 Sites 1144, 1146, and 1148, and IODP Leg 349 Sites U1431, U1432, U1433, and U1435 to study the sediment compaction and controls in the northern South China Sea. Sedimentation rate, sediment content, distribution area, and buried depth are the factors that influence sediment compaction in the deepwater basin of the South China Sea. Among these factors, the sediment content is the most important. The fitted normal compacted coefficients and mudline porosity for an interval of 50 m shows disciplinary variation versus depth. The pore pressure predicted from different fitted results shows varying overpressure situations. The normal compaction trend from Site 1144 reflects the porosity variation trend in stable deposition basins in the northern South China Sea. The predicted pore pressure shows overpressure at Site 1144, which is attributed to compaction disequilibrium. Nevertheless, the mixed lithology column may influence the predicted overpressure at Site 1148, which is responsible for the confusing result. Above all, we find that sediment compaction should serve as a proxy for pore pressure in the deepwater basin of the South China Sea.