Data mining and well logging interpretation: application to a conglomerate reservoir

Data mining is the process of extracting implicit but potentially useful information from incomplete, noisy, and fuzzy data. Data mining offers excellent nonlinear modeling and self-organized learning, and it can play a vital role in the interpretation of well logging data of complex reservoirs. We used data mining to identify the lithologies in a complex reservoir. The reservoir lithologies served as the classification task target and were identified using feature extraction, feature selection, and modeling of data streams. We used independent component analysis to extract information from well curves. We then used the branch-and- bound algorithm to look for the optimal feature subsets and eliminate redundant information. Finally, we used the C5.0 decision-tree algorithm to set up disaggregated models of the well logging curves. The modeling and actual logging data were in good agreement, showing the usefulness of data mining methods in complex reservoirs.

Pore structure effect on reservoir electrical properties and well logging evaluation

The reservoir pore structure controls the reservoir quality and resistivity response of hydrocarbon-bearing zones and thus, critically affects logging interpretation. We use petrophysical data in three types of reservoir with different pore structure characteristics to show that the complexity of pore structure had a significant effect on the effective porosity and permeability regardless of geological factors responsible for the formation of pore structure. Moreover,, the distribution and content of conductive fluids in the reservoir varies dramatically owing to pore structure differences, which also induces resistivity variations in reservoir rocks. Hence, the origin of low-resistivity hydrocarbon-bearing zones, except for those with conductive matrix and mud filtrate invasion, is attributed to the complexity of the pore structures. Consequently, reservoir-specific evaluation models, parameters, and criteria should be chosen for resistivity log interpretation to make a reliable evaluation of reservoir quality and fluids.

Acoustic reflection well logging modeling using the frequency-domain finite-element method with a hybrid PML

In this paper, we propose a hybrid PML （H-PML） combining the normal absorption factor of convolutional PML （C-PML） with tangential absorption factor of Mutiaxial PML （M-PML）. The H-PML boundary conditions can better suppress the numerical instability in some extreme models, and the computational speed of finite-element method and the dynamic range are greatly increased using this HPML. We use the finite-element method with a hybrid PML to model the acoustic reflection of the interface when wireline and well logging while drilling （LWD）, in a formation with a reflector outside the borehole. The simulation results suggests that the PS- and SP- reflected waves arrive at the same time when the inclination between the well and the outer interface is zero, and the difference in arrival times increases with increasing dip angle. When there are fractures outside the well, the reflection signal is clearer in the subsequent reflection waves and may be used to identify the fractured zone. The difference between the dominant wavelength and the model scale shows that LWD reflection logging data are of higher resolution and quality than wireline acoustic reflection logging.

Numerical simulation and dimension reduction analysis of electromagnetic logging while drilling of horizontal wells in complex structures

Electromagnetic logging while drilling(LWD)is one of the key technologies of the geosteering and formation evaluation for high-angle and horizontal wells.In this paper,we solve the dipole source-generated magnetic/electric fields in 2D formations efficiently by the 2.5D finite diff erence method.Particularly,by leveraging the field’s rapid attenuation in spectral domain,we propose truncated Gauss–Hermite quadrature,which is several tens of times faster than traditional inverse fast Fourier transform.By applying the algorithm to the LWD modeling under complex formations,e.g.,folds,fault and sandstone pinch-outs,we analyze the feasibility of the dimension reduction from 2D to 1D.For the formations with smooth lateral changes,like folds,the simplified 1D model’s results agree well with the true responses,which indicate that the 1D simplification with sliding window is feasible.However,for the formation structures with drastic rock properties changes and sharp boundaries,for instance,faults and sandstone pinch-outs,the simplified 1D model will lead to large errors and,therefore,2.5D algorithms should be applied to ensure the accuracy.

Acousto-electric well logging by eccentric source and extraction of shear wave

The nonaxisymmetric acousto-electric field excited by an eccentric acoustic source in the borehole based on Pride seismoelectric theory is considered. It is shown that the acoustic field inside the borehole, converted electric and magnetic fields and coupled fields outside the borehole are composed of an infinitude of multipole fields with different orders. The numerical results show that both the electromagnetic waves and the seismoelectric field in the borehole, and the three components of both electric field and magnetic field can be detected. Measurements on the borehole axis will be of advantage to determining shear velocity information. The components of the symmetric and nonsymmetric acoustic and electromagnetic fields can be strengthened or weakened by adding or subtracting the two full waveforms logged in some azimuths. It may be a new method of directly measuring the shear wave velocity by using the borehole seismoelectric effect.

Fractal Correction of Well Logging Curves

It is always significant for assessing and evaluation of oil bearing layers, especially for well logging data processing and interpretation of non marine oil beds to get more accurate physical properties in thin and inter thin layers. This paper presents a definition of measures and the measure presents power law relation with the corresponded scale described by fractal theory. Thus, logging curves can be reconstructed according to this power law relation. This method uses the local structure nearby concurrent points to compensate the average effect of logging probes and measurement errors. As an example, deep and medium induced conductivity (IMPH and IDPH) curves in ODP Leg 127 Hole 797C are reconstructed or corrected. Corrected curves are with less adjacent effects through comparison of corrected curves with original one. And also, the power spectra of corrected well logging curve are abounding with more resolution components than the original one. Thus, fractal correction method makes the well logging more resoluble for thin beds.

CCSD Well Logging Engineering Program

This paper introduces briefly the tasks and characteristics of China Continent Science Drilling (CCSD) Well Logging Engineering, the logging methods measured with CCSD, the quality control of original logging information, the logging plan of CCSD, the logging engineering management of CCSD, the logging interpretation and the results and reports made with CCSD.

Discrimination of Natural Fractures Using Well Logging Curve Unit

It is very difficult to discriminate natural fractures using conventional well log data, especially for most of the matured oilfields in China, because the raw data were acquired with relatively obsolete tools. The raw data include only GR and SP curves, indicative of lithology, AC curves, used to calculate the porosity of the formation, and a set of logging curves from various electrode length resistivity by laterolog. On the other hand, these oilfields usually have a large amount of core data which directly display the characteristics of the formation, and enough information of injection and production. This paper describes an approach through which logging curves are calibrated in terms of the raw data, and then a prototype model of natural fractures is established based on the investigation of core data from 43 wells, totaling 4 000 m in length. A computer program has been developed according to this method. Through analysis and comparison of the features of logging curves, this paper proposes a new concept, the well logging curve unit. By strictly depicting its shape through mathematical methods, the natural facture can be discriminated. This work also suggests an equation to estimate the probability of fracture occurrence, and finally other fracture parameters are calculated using some experimental expressions. With this methodology, logging curves from 100 wells were interpreted, the results of which agree with core data and field information.

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.

Flow pattern identification in oil wells by electromagnetic image logging

Petroleum production logging needs to determine the interpretation models first and flow pattern identification is the foundation, but traditional flow pattern identification methods have some limitations. In this paper, a new method of flow pattern identification in oil wells by electromagnetic image logging is proposed. First, the characteristics of gas-water and oil-water flow patterns in horizontal and vertical wellbores are picked up. Then, the continuous variation of the two phase flow pattern in the vertical and horizontal pipe space is discretized into continuous fluid distribution models in the pipeline section. Second, the electromagnetic flow image measurement responses of all the eight fluid distribution models are simulated and the characteristic vector of each response is analyzed in order to distinguish the fluid distribution models. Third, the time domain changes of the fluid distribution models in the pipeline section are used to identify the flow pattern. Finally, flow simulation experiments using electromagnetic flow image logging are operated and the experimental and simulated data are compared. The results show that the method can be used for flow pattern identification of actual electromagnetic image logging data.

Well logging evaluation of fine-grained hydrate-bearing sediment reservoirs: Considering the effect of clay content

Hydrate reservoirs are different from the host reservoirs of all other fossil energy sources because the characteristics of hydrate reservoirs are generally controlled by deep-sea fine-grained sedimentation. In such reservoirs, the reliability of the classical logging evaluation models established for diagenetic reservoirs is questionable. This study used well W8 in the Qiongdongnan Basin to explore the clay content, porosity, saturation, and hydrate-enriched layer identification of a logging-based hydrate reservoir, and it was found that considering the effect of the clay content on the log response is necessary in the logging evaluation of hydrate reservoirs. In the evaluation of clay content, a method based on the optimization inversion method can obtain a more reliable clay content than other methods. Fine-grained sediment reservoirs have a high clay content, and the effect of clay on log responses must be considered when calculating porosity. In addition, combining density logging and neutron porosity logging data can obtain the best porosity calculation results, and the porosity calculation method based on sonic logging predicted that the porosity of the studied reservoir was low. It was very effective to identify hydrate layers based on resistivity, but the clay distribution and pore structure will also affect the relationship between resistivity, porosity and saturation, and it was suggested that the factors effecting the resistivity of different layers should be considered in the saturation evaluation and that a suitable model should be selected. This study also considered the lack of clarity of the relationships among the lithology, physical properties, hydrate-bearing occurrence properties, and log response properties of hydrate reservoirs and the lack of specialized petrophysical models. This research can directly help to improve hydrate logging evaluation.

Simulation Experiments in Electromagnetic Tomography Well Logging in Two-phase Flow

Electromagnetic Computer Tomography （ECT） is a method to probe the interior of an inhomogeneous medium via surface measurement in a non-linear way. Due to the great differences in conductivity and permittivity between oil and water in the well, Electromagnetic Tomography Well Logging （ETWL）, a new flow imaging measurement system, is proposed to describe the distribution and movement of oil/water two-phase flow in the well by scanning the detected region and applying a suitable data processing algorithm. The results of the numerical simulation and physical modeling show that the system could provide a clear image of the flow profile.

Simulation logging experiment and interpretation model of array production logging measurements in a horizontal well

The distributions of local velocity and local phase holdup along the radial direction of pipes are complicated because of gravity differentiation,and the distribution of fluid velocity fi eld changes along the gravity direction in horizontal wells.Therefore,measuring the mixture flow and water holdup is difficult,resulting in poor interpretation accuracy of the production logging output profile.In this paper,oil–water two-phase flow dynamic simulation logging experiments in horizontal oil–water two-phase fl ow simulation wells were conducted using the Multiple Array Production Suite,which comprises a capacitance array tool(CAT)and a spinner array tool(SAT),and then the response characteristics of SAT and CAT in diff erent fl ow rates and water cut production conditions were studied.According to the response characteristics of CAT in diff erent water holdup ranges,interpolation imaging along the wellbore section determines the water holdup distribution,and then,the oil–water two-phase velocity fi eld in the fl ow section was reconstructed on the basis of the fl ow section water holdup distribution and the logging value of SAT and combined with the rheological equation of viscous fl uid,and the calculation method of the oil–water partial phase fl ow rate in the fl ow section was proposed.This new approach was applied in the experiment data calculations,and the results are basically consistent with the experimental data.The total fl ow rate and water holdup from the calculation are in agreement with the set values in the experiment,suggesting that the method has high accuracy.

Construction of well logging knowledge graph and intelligent identification method of hydrocarbon-bearing formation

Based on the well logging knowledge graph of hydrocarbon-bearing formation(HBF),a Knowledge-Powered Neural Network Formation Evaluation model(KPNFE)has been proposed.It has the following functions:(1)extracting characteristic parameters describing HBF in multiple dimensions and multiple scales;(2)showing the characteristic parameter-related entities,relationships,and attributes as vectors via graph embedding technique;(3)intelligently identifying HBF;(4)seamlessly integrating expertise into the intelligent computing to establish the assessment system and ranking algorithm for potential pay recommendation.Taking 547 wells encountered the low porosity and low permeability Chang 6 Member of Triassic in the Jiyuan Block of Ordos Basin,NW China as objects,80%of the wells were randomly selected as the training dataset and the remainder as the validation dataset.The KPNFE prediction results on the validation dataset had a coincidence rate of 94.43%with the expert interpretation results and a coincidence rate of 84.38%for all the oil testing layers,which is 13 percentage points higher in accuracy and over 100 times faster than the primary conventional interpretation.In addition,a number of potential pays likely to produce industrial oil were recommended.The KPNFE model effectively inherits,carries forward and improves the expert knowledge,nicely solving the robustness problem in HBF identification.The KPNFE,with good interpretability and high accuracy of computation results,is a powerful technical means for efficient and high-quality well logging re-evaluation of old wells in mature oilfields.

Analysis of Gas and Liquid Two-Phase Slug Flow Production Logging Interpretation Model in near Horizontal Shale Gas Wells

The development of shale gas reservoir is mainly based on horizontal well production.Slug flow of gas-liquid two-phase is invariably encountered in inclined wells and horizontal wells of a producing environment.Due to gravitational differentiation,oil-water two-phase flow pattern,the local velocity and local phase holdup along the radial direction of pipe in near horizontal wells will perform complicatedly.This paper presented the results of an experimental study and a theoretical analysis of two-phase gas/water flow in horizontal and highly inclined systems.Extensive experiments were conducted using a test loop made of 124 mm diameter acrylic pipe with inclination angles from the horizontal of 0°,5°,15°,45°,°2°,°5°and°10°,and with the total flow rate ranging from 50 to 800 m3/day.Based on the research on the law of slug flow dynamics model for gas-water two-phase flow in near horizontal pipeline,the theoretical analysis and experimental researches were done to propose the expressions of stable and exact production logging interpretation model for two-phase flow in near horizontal pipeline.The performance of the proposed method for estimating water holdup and water superficial velocity is in good agreement with our measurements.As a result,the slug flow dynamics model of gas-water two-phase flow in near horizontal wellbore was developed.The application effect of production logging in near horizontal wells had been improved.

Image Reconstruction for Invasive ERT in Vertical Oil Well Logging

An invasive electrical resistance tomographic sensor was proposed for production logging in vertical oil well.The sensor consists of 24 electrodes that are fixed to the logging tool,which can move in the pipeline to acquire data on the conductivity distribution of oil/water mixture flow at different depths.A sensitivity-based algorithm was introduced to reconstruct the cross-sectional images.Analysis on the sensitivity of the sensor to the distribution of oil/water mixture flow was carried out to optimize the position of the imaging cross-section.The imaging results obtained using various boundary conditions at the pipe wall and the logging tool were compared.Eight typical models with various conductivity distributions were created and the measurement data were obtained by solving the forward problem of the sensor system.Image reconstruction was then implemented by using the simulation data for each model.Comparisons between the models and the reconstructed images show that the number and spatial distribution of the oil bubbles can be clearly identified.

Application of Attribute Reduction to Well Logging

The quantity of well logging data is increasing exponentially, hence methods of extracting the useful information or attribution from the logging database are becoming very important in logging interpretation. So, the method of logging attribute reduction is presented based on a rough set, i.e., first determining the core of the information table, then calculating the significance of each attribute, and finally obtaining the relative reduction table. The application result shows that the method of attribute reduction is feasible and can be used for optimizing logging attributes, and decreasing redundant logging information to a great extent.

Influence of Logging Instrument Drag on Temperature Distribution in Horizontal Gas Wells

In order to clarify the influence of the instrument’s own drag on the temperature distribution in the horizontal gas wellbore in temperature logging.By constructing an indoor gas-liquid two-phase horizontal tube flow platform,the effects of the drag speed of the instrument on the temperature distribution in the wellbore were studied in the single-phase gas and gas-liquid two phases.In addition,during the process of instrument dragging,the influence of different perforation cluster opening methods and wellbore inclination on temperature distribution was also studied.The results show that the temperature fluctuation is reduced at higher drag speeds;Under a certain flow rate,the smaller the number of openings,the greater the influence of the instrument dragging inside the tube on the temperature distribution inside the tube;When the inclination angle is−5°,the drag of the instrument in the tube interferes greatly with the temperature distribution.When the inclination angle is 5°,the drag of the instrument in the tube has less interference with the temperature distribution.This study provides more reference for the future temperature calculation model of horizontal wellbore and has important research significance.

Utilizing NMR Mud Logging Technology To Measure Reservoir Fundamental Parameters in Well Site

Nuclear Magnetic Resonance mud logging technology (NMR mud logging) is a new mud logging technology. Mainly applies the CPMG(Carr-Purcell-Meiboom-Gill)pulse sequence to measure transverse relaxation time (T2) of the fluid. NMR mud logging can measure drill cutting, core and sidewall core in the well site, also according to the experiment results, the sample type and size has little effect to analysis result. Through NMR logging, we can obtain several petrophysical parameters such as total porosity, effective porosity, permeability, oil saturation, water saturation, movable fluid saturation, movable oil saturation, movable water saturation, irreducible fluid saturation, irreducible oil saturation, irreducible water saturation, pore size and distribution in rock samples, etc. NMR mud logging has been used nearly 10 years in China, Sudan, Kazakhstan, etc. it plays an important role in the interpretation and evaluation of reservoir and its fluids.

The Effect of Selective Logging on the Nest Density, Foraging Range and Colony Size on the Ground-Dwelling Ant Aphaenogaster Swammerdami Forel, 1886 in Kirindy ForestmMadagascar

Studying the ecology of ants can be a powerful tool for conservation, While the effect of logging is mainly investigated by the comparison of species richness and composition, the impact on individual species are often neglected. This study investigated the effect of selective logging on the nest density, foraging range and colony size on the ground-dwelling ant Aphaenogaster swammerdami in Kirindy forest--Madagascar. This ant is a common ground-dwelling species in Kirindy, a western dry deciduous forest of Madagascar. Sampling was done in two sites of the forest： One part that was selectively lodged and another that have not been logged. Here we show that selective logging led to a decrease in colony size and density, while the foraging range seemed to be unaffected. Higher desiccation stress and lower food availability in the logged forest are most likely to be responsible for these results.