The sensitivity of the array resistivity log to mud filtrate invasion and its primary five-parameter inversion for improved oil water recognition

In order to improve reservoir fluid recognition, the sensitivity of array resistivity response to the difference of the invasion properties in both oil-bearing layers and water layers is analyzed. Then the primary inversion is carried out based on the array resistivity log. The mud invasion process is numerically simulated based on the oil-water flow equation and water convection diffusion equation. The results show that the radial resistivity of a fresh mud-invaded oil-bearing layer presents complex distribution characteristics, such as nonlinear increase, increasing to decreasing and low resistivity annulus, and the resistive invasion profile of a water layer is monotonic. Under specific conditions, array resistivity log can reflect these changes and the array induction log is more sensitive. Nevertheless, due to the effect of factors like large invasion depth, reservoir physical and oil-bearing properties, the measured apparent resistivity may differ greatly from the actual mud filtrate invasion profile in an oil-bearing layer. We proposed a five-parameter formation model to simulate the complex resistivity distribution of fresh mud-invaded formation. Then, based on the principle of non-linear least squares, the measured array resistivity log is used for inversion with the Marquardt method. It is demonstrated that the inverted resistivity is typically non-monotonic in oil-bearing layers and is monotonic in water layers. Processing of some field data shows that this is helpful in achieving efficient reservoir fluid recognition.

Detection performance and inversion processing of logging-while-drilling extra-deep azimuthal resistivity measurements

We present systematic investigations on the physics,detection performance and inversion of logging-while-drilling extradeep azimuthal resistivity measurements(EDARM).First,the definitions of EDRAM measurements are discussed,followed by the derivation of the attenuation and phase-shift geometrical factors to illustrate the relative contributions of formation units to the observed signals.Then,a new definition of detection depth,which considers the uncertainty of inversion results caused by the data noise,is proposed to quantify the detection capability of ED ARM.Finally,the B ayesian theory associated with Markov chain Monte Carlo sampling is introduced for fast processing of EDARM data.Numerical results show that ED ARM is capable of detecting the azimuth and distance of remote bed boundaries,and the detection capability increases with increasing spacing and resistivity contrast.The EDARM tool can accommodate a large range of formation resistivity and is able to provide the resistivity anisotropy at arbitrary relative dipping angles.In addition,multiple bed boundaries and reservoir images near the borehole are readily obtained by using the Bayesian inversion.

Fast anisotropic resistivities inversion of loggingwhile-drilling resistivity measurements in highangle and horizontal wells

Information about anisotropic resistivity is essential in real-time correlation,updating of formation model and making more confi dent geosteering decisions in logging-while-drilling(LWD)application.However,abnormal responses such as curve separations and apparent resistivity“horns”often exist in the LWD resistivity measurements due to the infl uences of complex downhole environments.Thus,accurate formation resistivity is not readily available.In this paper,we present an effi cient inversion scheme for the rapid estimation of anisotropic resistivity from LWD resistivity measurements acquired in high-angle and horizontal wells.Several strategies are adopted in the inversion:(1)a one-dimensional(1D)simulator with a simplifi ed three-layered model guarantees the forward speed and keeps the number of inverted parameters as few as possible;(2)combined with geological and petrophysical bounds,the tool constraints derived from a detection capability analysis of LWD resistivity measurements are applied to scale down the inverted parameters’searching scope,which avoids meaningless solutions and accelerates the inversion signifi cantly;(3)multiple-initial guesses are used in the inversion to ensure a global solution.Inversion results over synthetic examples demonstrate that the proposed 1D inversion algorithm is well suited for complex formation structures.It is also robust and fast in extracting anisotropic resistivities from LWD resistivity measurements.

Electrical Structure of Wulingshan and Middle Jiangnan Orogen by Three-Dimensional Magnetotelluric Data Inversion

Funded by The National Key Research and Development Program of China,China Deep Exploration(Sinoprobe)and The China Geological Suvery Project on 2009–2019,a large scale magnetotelluric sounding(MT)survey grid(Fig.1)has covered whole south China.

Three-dimensional frequency-domain full waveform inversion based on the nearly-analytic discrete method

The nearly analytic discrete(NAD)method is a kind of finite difference method with advantages of high accuracy and stability.Previous studies have investigated the NAD method for simulating wave propagation in the time-domain.This study applies the NAD method to solving three-dimensional(3D)acoustic wave equations in the frequency-domain.This forward modeling approach is then used as the“engine”for implementing 3D frequency-domain full waveform inversion(FWI).In the numerical modeling experiments,synthetic examples are first given to show the superiority of the NAD method in forward modeling compared with traditional finite difference methods.Synthetic 3D frequency-domain FWI experiments are then carried out to examine the effectiveness of the proposed methods.The inversion results show that the NAD method is more suitable than traditional methods,in terms of computational cost and stability,for 3D frequency-domain FWI,and represents an effective approach for inversion of subsurface model structures.

Inversion of source mechanism of 1989 Loma Prieta earthquake by three-dimensional FEM Green's function

Based on three-dimensional joint finite element, this paper discusses the theory and methodology about inversionof geodetic data. The FEM and inversion formula is given in detail; also a related code is developed. By use of theGreen's function about 3-D FEM, we invert geodetic measurementS of coseismic deformation of the 1989 Ms=7. 1Loma Prieta earthquake to datermine itS source mechanism. The result indicates that the slip on the fault plane isvery heterogeneous. The maximum slip and shear stress are located about 10 kin to northwest of the eathquakesource, the stress drop is about more than 1 MPa.

Nonlinear Inversion for Complex Resistivity Method Based on QPSO-BP Algorithm

The significant advantage of the complex resistivity method is to reflect the abnormal body through multi-parameters, but its inversion parameters are more than the resistivity tomography method. Therefore, how to effectively invert these spectral parameters has become the focused area of the complex resistivity inversion. An optimized BP neural network (BPNN) approach based on Quantum Particle Swarm Optimization (QPSO) algorithm was presented, which was able to improve global search ability for complex resistivity multi-parameter nonlinear inversion. In the proposed method, the nonlinear weight adjustment strategy and mutation operator were used to enhance the optimization ability of QPSO algorithm. Implementation of proposed QPSO-BPNN was given, the network had 56 hidden neurons in two hidden layers (the first hidden layer has 46 neurons and the second hidden layer has 10 neurons) and it was trained on 48 datasets and tested on another 5 synthetic datasets. The training and test results show that BP neural network optimized by the QPSO algorithm performs better than the BP neural network without initial optimization on the inversion training and test models, and the mean square error distribution is better. At the same time, a double polarized anomalous bodies model was also used to verify the feasibility and effectiveness of the proposed method, the inversion results show that the QPSO-BP algorithm inversion clearly characterizes the anomalous boundaries and is closer to the values of the parameters.

Nonlinear inversion for electrical resistivity tomography based on chaotic DE-BP algorithm

Nonlinear resistivity inversion requires efficient artificial neural network(ANN)model for better inversion results.An evolutionary BP neural network(BPNN)approach based on differential evolution(DE)algorithm was presented,which was able to improve global search ability for resistivity tomography 2-D nonlinear inversion.In the proposed method,Tent equation was applied to obtain automatic parameter settings in DE and the restricted parameter Fcrit was used to enhance the ability of converging to global optimum.An implementation of proposed DE-BPNN was given,the network had one hidden layer with 52 nodes and it was trained on 36 datasets and tested on another 4 synthetic datasets.Two abnormity models were used to verify the feasibility and effectiveness of the proposed method,the results show that the proposed DE-BP algorithm has better performance than BP,conventional DE-BP and other chaotic DE-BP methods in stability and accuracy,and higher imaging quality than least square inversion.

Simulation of Rock Complex Resistivity Using an Inversion Method

The complex resistivity of coal and related rocks contains abundant physical property information,which can be indirectly used to study the lithology and microstructure of these materials.These aspects are closely related to the fluids inside the considered coal rocks,such as gas,water and coalbed methane.In the present analysis,considering different lithological structures,and using the Cole-Cole model,a forward simulation method is used to study different physical parameters such as the zero-frequency resistivity,the polarizability,the relaxation time,and the frequency correlation coefficient.Moreover,using a least square technique,a complex resistivity“inversion”algorithm is written.The comparison of the initial model parameters and those obtained after inversion is used to verify the stability and accuracy of such approach.The method is finally applied to primary-structure coal considered as the experimental sample for complex resistivity measurements.

An ICPSO-RBFNN nonlinear inversion for electrical resistivity imaging

To improve the global search ability and imaging quality of electrical resistivity imaging(ERI) inversion, a two-stage learning ICPSO algorithm of radial basis function neural network(RBFNN) based on information criterion(IC) and particle swarm optimization(PSO) is presented. In the proposed method, IC is applied to obtain the hidden layer structure by calculating the optimal IC value automatically and PSO algorithm is used to optimize the centers and widths of the radial basis functions in the hidden layer. Meanwhile, impacts of different information criteria to the inversion results are compared, and an implementation of the proposed ICPSO algorithm is given. The optimized neural network has one hidden layer with 261 nodes selected by AKAIKE's information criterion(AIC) and it is trained on 32 data sets and tested on another 8 synthetic data sets. Two complex synthetic examples are used to verify the feasibility and effectiveness of the proposed method with two learning stages. The results show that the proposed method has better performance and higher imaging quality than three-layer and four-layer back propagation neural networks(BPNNs) and traditional least square(LS) inversion.

Concealed porphyry delineation based on nonlinear three-dimensional densitydifference inversion: An example in the Beiya mine area, Western Yunnan, China

Intermediate acid-complex rock masses with low-density characteristics are the most important prospecting sign in the Beiya area, of western Yunnan province, and provide a physical basis for good gravity exploration. It is usually difficult to obtaining solutions in connection with actual geological situations due to the ambiguity of the conventional gravity-processing results and lack of deep constraints. Thus, the three-dimensional (3D) inversion technology is considered as the main channel for reducing the number of solutions and improving the vertical resolution at the current stage. The current study starts from a model test and performs nonlinear 3D density-difference inversion called “model likelihood exploration”, which performs 3D inversion imaging and inversion of the known model while considering the topographic effects. The inversion results are highly consistent with those of the known models. Simultaneously, we consider the Beiya gold mine in Yunnan as an example. The nonlinear 3D densitydifference inversion technology, which is restricted by geological information, is explored to obtain the 3D density body structure below 5 km in the mine area, and the 3D structure of the deep and concealed rock masses are obtained using the density constraints of the intermediate-acid-complex rock masses. The results are well consistent with the surface geological masses and drilling-controlled deep geological masses. The model test and examples both show that the 3D density-difference nonlinear inversion technology can reduce inversion ambiguity, improve resolution, optimize the inversion results, and realize “transparency” in deeply concealed rock masses in ore-concentrated areas,which is useful in guiding the deep ore prospecting.

Sea Water Intrusion Modeling in Rashid Area of Nile Delta (Egypt) via the Inversion of DC Resistivity Data

The current research focuses on the detection of sea water intrusion in Rashid area which is located about 75 km east to Alexandria, Egypt. For this purpose, geoelectrical survey was carried out using the Schlumberger Vertical Electric Sounding (VES) to identify freshwater thickness, sea water intrusion and estimate subsurface lithology. Seventeen VES stations were measured with current electrode separation (AB/2) ranging from 1.5 m to 100 m. Then, the VES data was interpreted using 1-D and 2-D inversion schemes of DC resistivity data based on least squares method with smoothness constrains. The inverted resistivity distribution at relatively shallow depth shows an important low resistivity zone that probably reflects salt water alteration zone (northern parts). Depth to the freshwater bearing layer reaches its maximum at the south and decreases towards the north. From quantitative interpretation, invasion of salt water started at depth about 10 m at north in the thickness of freshwater bearing layer ranging from 15 to 25 m, while at depth of about 120 m all the layers were saturated with salt water.

Inverse Spline Interpolation for All-time Resistivity of Central-Loop TEM

A convenient numerical calculation method (inverse spline interpolation) for all-time apparent resistivity intransient electromagnetic method (TEM) is proposed in this paper. Characteristic of early and late normalized inductiveelectromotive force was investigated. According to the turning point, the transient process is divided into the earlyphase, the turning point, and the late phase. Afterwards, apparent resistivity is obtained through inverse spline interpo-lation in the early and the late phases, respectively. Finally, the resistivities of the early-time and the late-time wereconnected together by the turning point. The result shows that the inverse spline method is feasible and the method alsolays a foundation for initial model construction in the TEM automatic inversion.

A robust behavior of Feed Forward Back propagation algorithm of Artificial Neural Networks in the application of vertical electrical sounding data inversion

The applications of intelligent techniques have increased exponentially in recent days to study most of the non-linear parameters. In particular, the behavior of earth resembles the non- linearity applications. An efficient tool is needed for the interpretation of geophysical parameters to study the subsurface of the earth. Artificial Neural Networks （ANN） perform certain tasks if the structure of the network is modified accordingly for the purpose it has been used. The three most robust networks were taken and comparatively analyzed for their performance to choose the appropriate network. The single- layer feed-forward neural network with the back propagation algorithm is chosen as one of the well- suited networks after comparing the results. Initially, certain synthetic data sets of all three-layer curves have been taken tk^r training the network, and the network is validated by the field datasets collected from Tuticorin Coastal Region （78°7＇30＂E and 8°48＇45＂N）, Tamil Nadu, India. The interpretation has been done successfully using the corresponding learning algorithm in the present study. With proper training of back propagation networks, it tends to give the resistivity and thickness of the subsurface layer model of the field resistivity data concerning the synthetic data trained earlier in the appropriate network. The network is trained with more Vertical Electrical Sounding （VES） data, and this trained network is demon- strated by the field data. Groundwater table depth also has been modeled.

A new method for earthquake prediction by earth-resistivity measurements

It is difficult to predict earthquakes by earthresistivity measurement with single-poleseparation. Taking a shallow seated horizontally stratification model, we developed a new measurement system with multipoleseparations and its corresponding inversion technique of the earth-resistivity to improve the prediction efficiency. Long-term experiments and investigations at several stations show that the new method based on resisti-vity variations at the bottom of shollow seated stratified medium is obviously superior to that directly based on the earth-resistivity itself.

Comparison of smoothness-constrained and geostatistically based cross-borehole electrical resistivity tomography for characterization of solute tracer plumes

Experiments using electrical resistivity tomography(ERT) have shown promising results in reducing the uncertainty of solute plume characteristics related to estimates based on the analysis of local point measurements only.To explore the similarities and differences between two cross-borehole ERT inversion approaches for characterizing salt tracer plumes,namely the classical smoothness-constrained inversion and a geostatistically based approach,we performed two-dimensional synthetic experiments.Simplifying assumptions about the solute transport model and the electrical forward and inverse model allowed us to study the sensitivity of the ERT inversion approaches towards a variety of basic conditions,including the number of boreholes,measurement schemes,contrast between the plume and background electrical conductivity,use of a priori knowledge,and point conditioning.The results show that geostatistically based and smoothness-constrained inversions of electrical resistance data yield plume characteristics of similar quality,which can be further improved when point measurements are incorporated and advantageous measurement schemes are chosen.As expected,an increased number of boreholes included in the ERT measurement layout can highly improve the quality of inferred plume characteristics,while in this case the benefits of point conditioning and advantageous measurement schemes diminish.Both ERT inversion approaches are similarly sensitive to the noise level of the data and the contrast between the solute plume and background electrical conductivity,and robust with regard to biased input parameters,such as mean concentration,variance,and correlation length of the plume.Although sophisticated inversion schemes have recently become available,in which flow and transport as well as electrical forward models are coupled,these schemes effectively rely on a relatively simple geometrical parameterization of the hydrogeological model.Therefore,we believe that standard uncoupled ERT inverse approaches,like the ones discussed and assessed in this paper,will continue to be important to the imaging and characterization of solute plumes in many real-world applications.

Exploring Sandstone Body in Weak Electrical Resistivity Contrast with AMT Data

AMT method with the economical and convenient superiority plays a key role in exploring the sandstone-type uranium deposits in China, which mainly meets to four problems such as the thickness of overlying strata, delineating the shape of the significant sand bodies, whether there are buried structures and knowing the basement relief. Exploring the sand body shape is the key one among such problems because sand body provides the room of uranium deposits and is the prerequisite for exploring uranium mineralization. Through an example of outlining the sandstone layer within the mudstone layers, the ability can be improved to recognize the electrical resistivity anomaly among the weak electrical property contrast by adjusting the inversion model’s scale. A route to deal with the problem was given by inverting different scale models followed by checking whether the anomalies of each inversion are reliable. Finally, the geo-electrical model was to be determined by comparing results of different scale model.

Three-dimensional lithospheric density distribution of China and surrounding regions

In this paper, we analyze lithospheric density distribution of China and surrounding regions on the basis of 30＇ × 30＇ gravity data and 1°×1 °P-wave velodty data, Firstly, we used the empirical equation be- tween the density and the P-wave velocity difference as the base of the initial model of the Asian lithospheric density. Secondly, we calculated the gravity anomaly, caused by the Moho discontinuity and the sedimentary layer discontinuity, by the Parker formula. Thirdly, the gravity anomaly of the spherical harmonics with 2 40 order for the anomalous body below the lithosphere is calculated based on the model of EGM96. Finally, by using Algebra Reconstruction Techniques （ART）, the inversion of 30＇ ~ 30＇ residual lithospheric Bouguer gravity anomaly caused by the lithosphere yields a rather detailed struc- tural model. The results show that the lithospheric density distribution of China and surrounding regions has a certain connection with the tectonic structure. The density is relatively high in the Philippine Sea plate, Japan Sea, the Indian plate, the Kazakhstan shield and the Western Siberia plain, whereas the Tibetan Plateau has low-density characteristics. The minimum value of density lies in the north of Philippines, in the Taiwan province and in the Ryukyu island arc.

Applications of variogram modeling to electrical resistivity data for the occurrence and distribution of saline groundwater in Domail Plain,northwestern Himalayan fold and thrust belt,Pakistan

This paper studies electrical resistivity dataset acquired for a groundwater study in the Domail Plain in the northwestern Himalayan section of Pakistan. Through a combination of geostatistical analysis,geophysical inversion and visualization techniques,it is possible to re-model and visualize the single dimension resistivity data into 2D and 3D space.The variogram models are utilized to extend the interpretation of the data and to distinguish individual lithologic units and the occurrence of saline water within the subsurface. The resistivity data has been calibrated with the lithological logs taken from the available boreholes. As such the alluvial system of the Domail Plain has formed during episodes of local tectonic activity with fluvial erosion and depositionyielding coarse sediments with high electrical resistivities near to the mountain ranges and finer sediments with medium to low electrical resistivities which tend to settle in the basin center. Thus a change is depositional setting happened from basin lacustrine environment to flash flooding during the Himalayan orogeny. The occurrence of rock salt in the northern mountains has imparted a great influence on the groundwater quality of the study area. The salt is dissolved by water which infiltrates into the subsurface through the water channels. Variogram aided gridding of resistivity data helps to identify the occurrence and distribution of saline water in the subsurface.

Application of high density resistivity method in accuracy of goaf detection

Based on the relationship between the diameter and buried depth of goaf,the authors establish the forward modeling by Res2dmod and inverse the model by Res2dinv. Thus,three kinds of models are obtained:the model of single resistivity anomalous body,model of double different distance resistivity anomalous body,and model of layered resistivity anomalous body. Using forward and inversion,the image of detection is simulated,and the reliability is proved by comparing with the engineering examples.