Acoustic Logging Research Articles

Allocation of Promising Objects for a Group of Deposits in the Karagay Saddle

This work completes the thorough petrophysical interpretation of 46 wells, as well as a technical feasibility analysis. Even though the acoustic logging was of very poor quality, work was done to get it ready for use in creating synthetic seismograms that accurately represented the section. The sle.28 Karagie Severny, which was drilled in 2012 and has significantly better GIS quality, was used to control this operation. Through a dynamic analysis, the shooting system's (footprint) influence on the distribution of the amplitudes at the Karagie Severny site was not eliminated during data processing, but it was removed during the re-processing. As a result, the findings for Karagie Severny should be taken with a grain of salt because the initial data's quality was not considered when choosing the sites for the suggested wells. However, the seismic facies analysis in two forms—classical and cluster—showed the presence of at least three primary facies complexes, which are reflected in both formed, with a more precise distribution in accordance with cluster analysis.

Reservoir Porosity Improvement Device based on Underwater Pulse Arc Fracturing and Frequency Resonance Technology

SummaryThe low porosity of the reservoir has a significant impact on the production of unconventional oil and gas, hence a device to increase reservoir porosity and enhance unconventional oil and gas recovery was developed. The device can be lowered to 3000 m and operate continuously for more than 30 minutes under a discharge voltage of 11 kV in the frequency range of 0–60 Hz to improve reservoir porosity by causing reservoir resonance. The equipment structure includes an energy storage circuit, trigger switch, and energy transducer. The theoretical model of the energy storage circuit was established by the state space averaging method to obtain the time constant which was verified by a simulation experiment. The gas spark switch with an adjustable gap was used, the frequency control of the discharge pulse was achieved by rectifier voltage regulation, and the underwater pulse arc fracturing experiment was performed to confirm the accuracy and stability of the frequency control. Additionally, the effect of frequency resonance on reservoir porosity improvement was examined through comparative experiments, and the images of the distribution of pore texture in shale obtained by the X-ray computed tomography (CT) system demonstrate that resonance excitation can significantly promote the development of fractures and the improvement of shale samples’ porosity. The stimulation operation field experiment was carried out on coalbed methane wells in Shanxi Province, and the multipole array acoustic logging image verified that the equipment has a good reservoir porosity improvement effect. Experimental results indicate that this study has a potential application value in the field of unconventional reservoir stimulation.

Design of an Acoustic Through-Casing Logging Tool.

Well logging is performed in oil and gas exploration wells to obtain the physical characteristics of underground formations. Thereafter, these wells are cased. Through-casing logging is important in mature fields and for wells that are cased without logging due to borehole stability issues. Acoustic through-casing logging is a challenging issue due to the strong interference of casing waves in formation waves, especially when the casing and formation are poorly bonded. An acoustic tool with dual-source transmitters is developed, in which an additional transducer is added to suppress casing waves. First, the operation principle and the overall design of the tool are carried out, including the span distance between the two transmitting transducers and the spacing distance between the transmitting transducer and the receiving transducers. Thereafter, a dual-source transmitting circuit is designed to send out two excitation signals of opposite polarities. These signals possess good consistency, high emission power, and precise signal adjustment. Lastly, the tool is tested in cased exploration wells in China. The experiment endings show that about 90% of the casing waves are canceled. By suppressing the casing wave amplitude, the cased-hole acoustic logging can be used commercially to obtain trustworthy formation information.

Borehole radiation and reception responses for azimuthal shear-wave reflection imaging with an off-centred dipole acoustic tool

Abstract Radiation and reception responses of a dipole acoustic logging tool placed eccentrically in borehole fluid are an interesting and important topic in acoustic reflection imaging. Herein, we present a thorough research study on these responses. We treat the wave incidence from the reflector as the radiation from a virtual source and use the cylindrical-wave expansion method to solve both the wave radiation and reception problems for the off-centred tool, which, by using the steepest-descent method, yields asymptotic solutions for modelling the radiation and reception wavefield characteristics. The modelling results from the analytical solution and the 3D finite-difference method were in good agreement. Specifically, we analysed the radiation directivity of an eccentric dipole source in a fluid-filled borehole. The results revealed that the radiation pattern was asymmetric with respect to the borehole, and the asymmetry was determined by the eccentric distance, source frequency and formation properties. In particular, for the typical 3 kHz dipole logging frequency, the radiation was stronger in the off-centred direction than in the opposite direction. The asymmetry of the eccentric radiation resulted in a significant amplitude difference relative to its centred counterpart, which provided a potential method for addressing the 180° azimuth ambiguity of the dipole source. We used a theoretical waveform modelling example to demonstrate this advantage. Therefore, the results of this study provide a theoretical foundation for the development and application of dipole shear-wave imaging technology.

Genetic Mechanisms and Identification of Low-Resistivity Pay Zones: A Case Study of Pengyang Area, Ordos Basin, China

The Triassic Yanchang Formation in the Pengyang area of Ordos Tianhuan depression is an important oil and gas formation. However, most of the oil pays in the study formations are low-resistivity or low-contrast reservoirs with low permeability, bringing challenges to the reservoir identification and evaluation by well logs. In this paper, we first measured the nuclear magnetic resonance (NMR), phase permeability, cation exchange capacity (CEC), and X-ray diffraction for core samples. Then, the genetic types for the low-resistivity pays were analyzed based on the experiment results, water analysis, and well log data collected. It was found that large variations of formation water salinity, high irreducible water saturation, and clay conductivity are the primary genetic types. Further, the random forest (RF) algorithm with sensitive parameter inputs was used to identify the oil, oil and water, and water layers. The anomaly of spontaneous potential (∆SP) that characterizes water salinity, the relative value of gamma ray log (∆GR) that describes the bound water content, resistivity, density, and acoustic logs were taken as sensitive logs according to the genetic analysis. Finally, this identification method was verified by comparison with the traditional crossplot method and oil test results. The identification accuracy of the RF is 90%, far higher than that by the crossplot method.

Measurement resolution of acoustic reflection imaging logging with a cylindrical phased array acoustic receiver station

Azimuthal acoustic reflection imaging logging plays an important role in the exploration and development of fracture-cavity reservoirs, because it can image geological structures within tens of meters around the borehole. However, minimal evaluations have been conducted for the detection of small-scale geological anomalies, particularly the simultaneous measurement of multiple small-scale scatterers. In this study, the scanning-reception implementations of phased array acoustic receiver stations in the Borehole Azimuthal Acoustic Reflection Imaging Tool (BAR) were developed based on the beamforming principle. The measurement responses of BAR were simulated and the scanning-reception performances of arcuate phased array (APA) and cylindrical phased array (CPA) acoustic receiver stations were compared using a three-dimensional (3D) finite difference algorithm for one or two small-scale caves in a formation away from a fluid-filled borehole. The azimuth and elevation measurement resolutions of CPA acoustic receiver stations were determined by analyzing the scattered wavefields under the circumstances of two caves on the same horizontal or vertical plane. Numerical simulation results showed that the echo waves scattered from small-scale caves were similar to those reflected by large-scale formation interfaces outside the borehole. The azimuth angle of a single cave could be obtained by calculating the amplitudes of P–P echoes at different azimuths received by the APA acoustic receiver station. Compared with the APA scanning-reception mode, the 3D scanning-reception mode based on the CPA acoustic receiver station was more applicable when two caves were simultaneously located outside the borehole. Under the calculation conditions of this study, the CPA acoustic receiver station had a limit azimuth resolution of ∼60°–90° and a limit elevation resolution of ∼8.8°–17.4° when two scatterers were located on the same horizontal or vertical plane. This work verified the superiority of the CPA scanning-reception mode for the detection of small-scale geological anomalies and provided a theoretical basis for the wider application of BAR.

Cement logs evaluation Ghadames Basin, (Al Wafa Gas field), case study, Libya

The acoustic logging method is the most commonly used to qualify a cement job. It can be run several hours or several days after the cement placement and evaluates the quality of the bond (acoustic coupling) between the casing, the cement and the formation. It measures the attenuation of the sound signal as it propagates through the casing, cement and formation and returns to the sensor. This technique and will help spot free pipe, partially bonded or fully bonded pipe. The aim of this paper is analyses and evaluates cement logs data in two wells within Al Wafa Gas field, the cement logs analysis results of two wells shown variables cement condition behind the casing. The well A24-NC169A, analysis showing a good cement condition for both casing and formation as the signature of cement logs showing very low amplitude reading due to high attenuation of waves in cement bound log because the cement was good behind casing. The well A56-NC169A, showing variable results, as good cement condition behind the casing bond to casing, formation, micro- annual and channeling condition. The gamma- ray ranging from 40 to 150, as sand to shaly sand sediments, transit-time was normal, cement bound log recorded variables from low, medium to high amplitude (18 to 56) due to different wave attenuated depending on cement condition (good to partially cement). Variable density log showing variable results (Formation arrive, casing arrive, no casing arrive and no formation arrive, all depending on cement behind the casing. In general, the results revealed good cement condition.

Acoustic logging response law in shales based on petrophysical model

Shale acoustic logging response law is complex due to the multiple minerals and pores, which limits the application of acoustic logging in shale reservoir parameter evaluation, therefore clarifying the shale acoustic logging response law is of great importance. Different petrophysical models are adopted for the equivalence of organic matter, clay, matrix minerals, and fractures, in Wufeng-Longmaxi shale formation in the Jiaoshiba area. Finally, the self-consistent approximation model is used to combine different components, and a shale petrophysical model with a complex pore structure is constructed. The model verification results show it has good predictability for shale. Based on the model, the effect of different mineral compositions and different types of pores are studied. The results show that: 1) The effect of clay and organic matter is very complex, and the variation laws of layered clay (organic matter) and dispersed clay (organic matter) on the acoustic wave are consistent. 2) Layered clay or organic matter leads to the formation anisotropy increase, which makes the acoustic time difference greater than that of containing dispersed clay (organic matter). 3) The fracture is the main control factor of anisotropy, and the anisotropy of gas-bearing fracture is higher than that of water/oil fracture.

A Novel Method of Deep Learning for Shear Velocity Prediction in a Tight Sandstone Reservoir

Shear velocity is an important parameter in pre-stack seismic reservoir description. However, in the real study, the high cost of array acoustic logging leads to lacking a shear velocity curve. Thus, it is crucial to use conventional well-logging data to predict shear velocity. The shear velocity prediction methods mainly include empirical formulas and theoretical rock physics models. When using the empirical formula method, calibration should be performed to fit the local data, and its accuracy is low. When using rock physics modeling, many parameters about the pure mineral must be optimized simultaneously. We present a deep learning method to predict shear velocity from several conventional logging curves in tight sandstone of the Sichuan Basin. The XGBoost algorithm has been used to automatically select the feature curves as the model’s input after quality control and cleaning of the input data. Then, we construct a deep-feed neuro network model (DFNN) and decompose the whole model training process into detailed steps. During the training process, parallel training and testing methods were used to control the reliability of the trained model. It was found that the prediction accuracy is higher than the empirical formula and the rock physics modeling method by well validation.

Improving the 3D facies model with the seismic-derived log volumes: a case study from the Asmari Formation in the Hendijan Field, southwest Iran

Abstract The prolific Oligocene-Miocene Asmari Formation is the primary reservoir rock hosting important hydrocarbon resources in Iran and consists of fluvial/deltaic siliciclastic and shallow marine carbonate rocks in the Hendijan Field. Due to the significant facies variability of the formation, the presence and quality of the reservoir pose a significant uncertainty in the characterization of the reservoir. This study compares two facies models, one based on well logs only and the second based on estimated facies volumes as a secondary variable in facies modelling. The petrophysical evaluation with microscopic thin sections and electrofacies analysis were used to classify the facies and determine the reservoir quality. As a result, the Ghar Member was identified as a highly porous interval, while the lower part of the Asmari Formation is characterized by tight facies. A sequential Gaussian simulation (SIS) algorithm was used to build the 3D facies model on the basis of the well logs. Acoustic impedance, shear impedance and density (derived from pre-stack inversion) were used as inputs to an artificial neural network to generate acoustic and density log volumes. Using electrofacies cut-offs, facies volume was constructed and used as a secondary variable to improve the initial facies model. The final facies model was compared with the blind well to check the validity of the prediction and satisfactory results were obtained. Since the values are present in all the cells of the reservoir (the traditional facies model only has values for the well location), the estimated facies volume is an accurate variable in the prediction of the facies model for the Asmari reservoir and for this reason the secondary facies model is more reliable than the primary one.

Hydrocarbon Reservoir Characterization Using Well Logs of Nahr Umr Formation in Kifl Oil field, Central Iraq

This study aims to determine the petrophysical characteristics of the three wells in the Kifl Oilfield, central Iraq. The well logs were used to characterize hydrocarbon reservoirs to assess the hydrocarbon prospectivity, designate hydrocarbon and water-bearing zones, and determine the Nahr Umr Formation's petrophysical parameters. The Nahr Umr reservoir mainly consists of sandstone at the bottom and has an upper shale zone containing a small proportion of oil. The geophysical logs data from three oil wells include gamma-ray, resistivity, neutron, density, acoustic, and spontaneous potential logs. A gamma-ray log was employed for lithology differentiation, and a resistivity log was used to determine the response of distinct zones' productivity. The petrophysical parameters of shale volume, total porosity, effective porosity, water saturation, hydrocarbon saturation, and flushed zone saturation were evaluated using computer processing analyses (CPI). These parameters were plotted by interactive petrophysics (IP) software. The effective porosity (PHE) in the sandstone unit ranges between 3.2 and 31.2%, water saturation (SW) ranges between 6.6 and 100%, and hydrocarbon saturation and (Sh) range from 6 to 65%. The Nahr Umr Formation has moderate to low reservoir characteristics in the lower sandstone unit.

Fracture stratigraphy and mechanical stratigraphy in sandstone: A multiscale quantitative analysis

Mechanical stratigraphy can provide valuable knowledge for evaluating and predicting the distribution of structural fractures and in situ stress. The fracture stratigraphy and mechanical stratigraphy of the Triassic Yanchang Formation sandstone reservoirs in the Huaqing area of the Ordos Basin were investigated. In this study, borehole images were used to identify and characterize the orientation and properties of natural fractures, and array acoustic logs were used to analyze the rock mechanical properties. By considering the positional and scale cycles, the mechanical stratigraphy and areal fracture density at multiple scales were calculated, and the statistical correlation between them was analyzed. The results show that when the dynamic Young's modulus is less than 45 GPa, the areal fracture density generally increases with increasing Young's modulus; when the dynamic Young's modulus is greater than 48.5 GPa, the areal fracture density decreases with increasing dynamic Young's modulus. Additionally, the areal fracture density peaks when the dynamic Young's modulus is in the range of 45–48.5 GPa. In general, the dynamic Poisson's ratio is negatively correlated with the areal fracture density at multiple scales; when the dynamic Poisson's ratio is less than 0.24, the areal fracture density rapidly decreases as the dynamic Poisson's ratio increases; when the dynamic Poisson's ratio is greater than 0.24, the dynamic Poisson's ratio is only weakly correlated with the areal fracture density. The fitting results between the mechanical stratigraphy and areal fracture density show that the mathematical model relating these two parameters is related to the statistical scale.

Study on acoustic logging response of fractured reservoirs using a novel equivalent medium model

Study on acoustic logging response of fractured reservoirs using a novel equivalent medium model

A combined method for gas-bearing layer identification in a complex sandstone reservoir

Langgu Depression is a mature oil and gas exploration area with complicated lithological and physical properties. The varying formation fluid, low-resistivity hydrocarbon-bearing reservoirs, and non-uniform logging series greatly increase the difficulty of gas reservoir identification. The Monte Carlo method is employed to simulate the neutron–gamma logging responses to gas saturation and the influential factors. According to the result, a new gas identification chart eliminating the influence of porosity and formation water salinity is proposed to identify gas reservoirs in the old wells. At the same time, a fluid factor extracted from array acoustic logging and core measurement data is sensitive to the development of gas-bearing layers and useful for the identification of gas reservoirs in the new wells with array acoustic logging. The field examples show that the new combined method greatly improves the ability to identify gas-bearing layers and works well in old well reexamination and new well interpretation.

A preliminary study on wellbore flow interpretation of fiber optic vibration signals based on K-means clustering algorithm

The wellbore flow analysis of optical fiber vibration signal depends on distributed optical fiber logging. Distributed optical fiber logging technology identifies the fluid in the well through distributed optical fiber acoustic sensor (DAS) and distributed optical fiber temperature sensor (DTS). Distributed optical fiber sensor has the advantages of small underground interference, high efficiency and low cost. In this paper, the wellhead data extracted by the distributed optical fiber acoustic sensor is used to calculate the upper bound of the fluid sound frequency band in the pipe by nonlinear least squares fitting. The K-means clustering algorithm is used to cluster the optical fiber vibration signals in the low frequency band. According to the clustering results, the ratio of the optical fiber signal eigenvalues of each production layers is obtained, and the trend of the ratio of the optical fiber signal eigenvalues of each production layers is judged to be close to the trend of the water absorption intensity. Compared with traditional acoustic logging, the wellbore flow analysis using distributed optical fiber acoustic sensor can quickly determine the production contribution of each layer and the change of fluid phase state in the production cycle. Combined with traditional production logging technology, distributed optical fiber logging shows its reliability and accuracy in data collection, logging interpretation and production application. Starting from the principle of distributed optical fiber acoustic sensing technology, this paper briefly expounds the properties of distributed optical fiber acoustic sensor and the principle of injection profile logging, systematically introduces the processing of distributed optical fiber acoustic data, and emphatically introduces the accuracy of K-means clustering algorithm for analyzing distributed optical fiber acoustic signal and qualitative judgment of production layer, which provides a new idea for judging the accuracy of production layers.

Machine-learning-based automatic well-log completion and generation: Examples from the Ordos Basin, China

Oilfields have large amounts of old well-logging data, some of which were possibly lost or distorted for borehole situation, limiting the use of well-logging in formation evaluation. Machine-learning algorithms provide possibility to complete or correct bad quality logging, even to generate new loggings. We took 50 wells in the Ordos Basin, a prolific hydrocarbon production basin, as an example to complete and generate well- loggings. We applied three algorithms, such as random forest (RF), extreme gradient boosting (XGBoost), and deep neural network (DNN) algorithm, for well-logging curve completion experiments. We generated resistivity loggings including deep investigate lateral resistivity log (RILD) and medium investigate lateral resistivity log (RILM) using four loggings, e.g. the spontaneous potential (SP), gamma ray (GR), acoustic log (AC), and electrical resistivity log (R4). After data preprocessing, we used training data sets and validation data sets, accounting for 90% and 10% of all database, respectively, to complete and generate well-logs. The results reveal that the XGBoost algorithm has a better effect on well-log completion if the parameters used are sufficiently optimized with experience, whereas the DNN algorithm has great advantages if large sufficient amounts of well-log data sets are available in the training sets. In this experiment, the accuracy of results by RF algorithm is better than those by XGBoost algorithm because the optimized parameters are difficult to guarantee without experience, and better than that, by DNN algorithms in which the input number of wells is less than 300 and may not be sufficient. In addition, RF algorithm has wider expansibility, higher efficiency, lower computation requirements, and better generalization ability. Our work provides a better understanding of the conditions and function of the application of different machine-learning algorithms to well-logging completion and generation.

Methods for determining the characteristics of weathered granite reservoirs: application to Binxian Uplift, Dongying Sag, Bohai Bay Basin

AbstractWith the discovery of high-productivity oilfields in granite buried hills, it is necessary to systematically investigate the types of granite weathered reservoirs at different depths and their spatial distribution. However, previously subdivided reservoirs have been assumed to exhibit the same vertical zoning in different structural parts, contradicting the fact that the degree of weathering varies with the topography. In addition, comprehensive and quantitative methods for classifying reservoir types are lacking. Taking the Binxian Uplift of the Dongying depression in Bohai Bay Basin as an example, we therefore established a comprehensive identification standard for dividing granite reservoirs using lithology division, logging curve statistics, a dual-medium matrix–fracture model and seismic facies identification. Subsequently, by combining logging and seismic methods, the vertical stacking types and distribution properties of weathered granite reservoirs in various structural positions were analysed. The reservoirs were divided vertically into three zones: regolith, dissolution and fracture. Quantitative logging response standards for the different reservoirs were established using acoustic, density, natural gamma and resistivity logging. In terms of the seismic response, the regolith, dissolution and fracture zone corresponded to high-, medium- and low-amplitude seismic facies, respectively. A dynamic double-layer structure of the reservoir was established, comprising a completely weathered layer and a semi-weathered layer. The reservoir division method proposed in this paper can be used in other areas, and the research results can help promote the exploration of granite buried hill reservoirs.

New insights into permeability determination by coupling Stoneley wave propagation and conventional petrophysical logs in carbonate oil reservoirs

The need to determine permeability at different stages of evaluation, completion, optimization of Enhanced Oil Recovery (EOR) operations, and reservoir modeling and management is reflected. Therefore, various methods with distinct efficiency for the evaluation of permeability have been proposed by engineers and petroleum geologists. The oil industry uses acoustic and Nuclear Magnetic Resonance (NMR) loggings extensively to determine permeability quantitatively. However, because the number of available NMR logs is not enough and there is a significant difficulty in their interpreting and evaluation, the use of acoustic logs to determine the permeability has become very important. Direct, continuous, and in-reservoir condition estimation of permeability is a unique feature of the Stoneley waves analysis as an acoustic technique. In this study, five intelligent mathematical methods, including Adaptive Network-Based Fuzzy Inference System (ANFIS), Least-Square Support Vector Machine (LSSVM), Radial Basis Function Neural Network (RBFNN), Multi-Layer Perceptron Neural Network (MLPNN), and Committee Machine Intelligent System (CMIS), have been performed for calculating permeability in terms of Stoneley and shear waves travel-time, effective porosity, bulk density and lithological data in one of the naturally-fractured and low-porosity carbonate reservoirs located in the Southwest of Iran. Intelligent models have been improved with three popular optimization algorithms, including Coupled Simulated Annealing (CSA), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA). Among the developed models, the CMIS is the most accurate intelligent model for permeability forecast as compared to the core permeability data with a determination coefficient (R2) of 0.87 and an average absolute deviation (AAD) of 3.7. Comparing the CMIS method with the NMR techniques (i.e., Timur-Coates and Schlumberger-Doll-Research (SDR)), the superiority of the Stoneley method is demonstrated. With this model, diverse types of fractures in carbonate formations can be easily identified. As a result, it can be claimed that the models presented in this study are of great value to petrophysicists and petroleum engineers working on reservoir simulation and well completion.

Acoustic image log facies and well log petrophysical evaluation of the Barra Velha Formation carbonate reservoir from the Santos Basin, offshore Brazil

Acoustic image log facies and well log petrophysical evaluation of the Barra Velha Formation carbonate reservoir from the Santos Basin, offshore Brazil

Estimation of horizontal stresses from wellbore failures in strike-slip tectonic regime: A case study from the Ordovician reservoir of the Tinzaouatine field, Illizi Basin, Algeria

We present a geomechanical analysis of the Ordovician reservoir from the Tinzaouatine field situated in the prolific Illizi Basin, eastern Algeria. The sandstone reservoir has a hydrostatic pore pressure gradient (9.95 MPa/km). We analyzed a cumulative of 300 m of acoustic image log data and identified the coexistence of B-quality extensive drilling-induced tensile failures (DITFs) and compressive failures, i.e., breakouts (BOs), indicating a mean maximum horizontal stress ([Formula: see text]) orientation of N140°E. We used a combined BO and DITF-based solution to estimate horizontal stress magnitudes when the two failure types coexist. Based on the C-quality minifrac measurements, we interpreted the minimum horizontal stress ([Formula: see text]) gradient as 17.4–17.47 MPa/km, whereas the new approach indicates an [Formula: see text] range of 17.31–18.67 MPa/km. Using the BO width and DITF-based approaches, we inferred an [Formula: see text] gradient range of 28.37–38.59 MPa/km within the studied reservoir. Based on the relative stress magnitudes, we infer a strike-slip tectonic stress regime in the studied field.