Sonic Logs Research Articles

3D Near-surface Velocity Model Building by Integrating Surface, Borehole Seismic, and Well-logging Data in a Small-scale Testbed

This study aims to build a 3D velocity model for investigating and evaluating underground contaminants flowing through groundwater pathways. To accomplish this goal, we performed seismic exploration at a test site with fractured rock layers within a depth of 100 m. The acquired seismic data was then used to construct a three-dimensional (3D) P-wave velocity model of the test site. Although comprehensive geophysical exploration may be useful for investigating the near-surface structure, this paper focuses only on constructing a P-wave velocity model using the seismic method. The primary information of the model consists of extracted velocities from a two-dimensional surface, borehole first-arrival traveltime tomography results, and full waveform sonic log data. Since the test site has the spatial restriction of the survey line, we intended to improve the geological structure analysis results using various quantitative and qualitative analysis methods. First, to increase the reliability of velocity information, we performed a traveltime analysis on the zero vertical interval (ZVI) gather from the borehole seismic data. Then, we identified the qualitative information of the fracture zone's location by analyzing the amplitude variation of the ZVI gather. Moreover, we extracted structural information using the common reflection point gather from the borehole seismic data to supplement the obtained lithological information. However, the information for constructing a 3D P-wave velocity model was still insufficient due to the spatial constraints of the survey line and the limited depth of the borehole seismic survey. We filled this gap using the radial basis function interpolation method. We could verify the completed 3D P-wave velocity model by comparing it with core log data. Overall, the integrated interpretation of the final velocity model and the analysis results could provide a probable pathway that indicates hydraulic connectivity.

Heterogeneity Versus Anisotropy and the State of Stress in Stable Cratons: Observations From a Deep Borehole in Northeastern Alberta, Canada

AbstractGeophysical logs collected from a deep borehole drilled into the North American Craton in Northeastern Alberta shed valuable light on the state of stress in stable cratons. Observed breakout (BO) azimuths rotate between three depth intervals, ranging from 100° at 1,650–2,000 m to 173° at 2,000–2,210 m, and finally to 145° at the bottom. No apparent fractures that might have disturbed the stress field were found. Two potential causes of these rotating BOs can be either a heterogeneous stress field or elastic and strength anisotropy of the formation. The latter interpretation is favored since observed BO azimuths are strongly controlled by rock metamorphic textures, as validated by their close correlations with dip directions of foliation planes and polarization directions from dipole sonic logs. Monte Carlo realizations further demonstrate that anisotropic metamorphic rocks subjected to a uniform horizontal stress direction could result in the observed azimuth‐rotating BOs. Stress magnitudes inferred from this analysis, which incorporates rock anisotropy and weak foliation failure planes, suggest a normal faulting regime and a maximum horizontal compressive direction consistent with that in the overlying Western Canadian Sedimentary Basin (NE‐SW) and the motion of the North American plate. The inferred stress magnitudes are low and Mohr‐Coulomb analyses demonstrate that the formation is not near the critical condition for slip on weak planes. However, more detailed investigations should be conducted since Monte Carlo calculations indicate that analyses from BO widths, particularly when a conventional Kirsch‐based formula is employed, are highly nonunique, allowing for large variations in potential stress states.

Study Investigates Casing Wear in the Culzean Field

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 206221, “Casing Wear: Prediction, Monitoring, Analysis, and Management in the Culzean Field,” by Florian Aichinger, SPE, Loic Brillaud, SPE, and Ben Nobbs, SPE, H&P Technologies, et al. The paper has not been peer reviewed. _ This paper presents predicted vs. measured wear for six wells in the Culzean field, a high-pressure/high-temperature (HP/HT) gas condensate field in the central North Sea. The focus of the complete paper is on the monitoring and analyzing process, particularly how to use offset data to improve accuracy of casing-wear prediction. Field and Well Background Wells in the Culzean field are quite deep, with a measured depth (MD) of 15,000–16,500 ft, and are J-shaped with a slight sail angle (inclination 30–40°). These features result in significant tension loads at the buildup and, potentially, at unplanned curvatures in the vertical section. Combined with possibly high rotating hours, these factors create a considerable risk of high casing wear. Additionally, a challenging pressure regime is present. The steep pressure-transition zone (PTZ) overlying the target reservoir, and the expected predrilled narrow mud-weight window between the pore pressure and formation at the top of the Pentland reservoir of 0.060 ppg, called for a new well-design approach. To address this challenge, the production casing was designed as a 10-in. production liner and a 10¾×10-in. tieback production string. The well design and operations plan required drilling both 12¼- and 8½-in. sections without the 10¾×10-in. tieback production string installed. Consequently, the 14×13⅝-in. intermediate casing could be exposed to higher pressures than usual. Extensive work was performed to enhance casing-wear prediction and to determine the likelihood of failure if a well-control risk materialized. The 12¼-in. section and 10-in. production liner shoe were placed as deeply as possible into the PTZ in the Upper Valhall/Tuxen formation. An appreciable risk was the possibility of a kick while drilling the 12¼-in. section from the Pentland reservoir. The most extreme well-control event the 14×13⅝-in. intermediate casing could experience, however, would have been a well-full-of-gas event while drilling the 8½-in. section. The assessment of the risk associated with such an event was addressed by careful attention to an assessment of casing wear and remaining casing wall thickness and the probability of failure of the 14×13⅝-in. casing, assuming that the casing was worn. The failure-probability assessment of the 14×13⅝-in. intermediate casing was performed using a reliability-based design approach using survival design principles and probability-of-failure estimation. Methodology: Wear Computation and Measurement Analysis of casing wear between a drillstring and the inner surface of casing requires application of an appropriate casing-wear model. A stiff-string model, as used in this work, is advantageous because it can consider pipe clearance, pipe stiffness, and axial and radial casing contact-point location. The simulation uses an adaptable 3D mesh, allowing the calculation of wear in all radial orientations for every chosen MD. The multifinger-caliper-log (MFCL) interpretation methodology uses inner-diameter measurements to calculate an ellipse that best fits the casing shape. The methodology does not require a base log and increases accuracy compared with the traditional method of comparing the maximum inner diameter of MFCL logs taken before and after drilling. The methodology also can be applied to sonic logs as a second information source apart from the direct wall-thickness measurement if the latter is not available. A detailed overview of this process is included in the complete paper.

Estimation of Petrophysical Properties for Zubair Reservoir in Abu-Amood Oil Field

The petrophysical analysis is significant to determine the parameters controlling the production wells and the reservoir quality. In this study, Using Interactive petrophysics software to analyze the petrophysical parameters of five wells penetrated the Zubair reservoir in the Abu-Amood field to evaluate a reservoir and search for hydrocarbon zones. The available logs data such as density, sonic, gamma ray, SP, neutron, and resistivity logs for wells AAm-1, AAm-2, AAm-3, AAm-4, and AAm-5 were used to determine the reservoir properties in Zubair reservoir. The density-neutron and neutron-sonic cross plots, which appear as lines with porosity scale ticks, are used to distinguish between the three main lithologies of sandstone, limestone, and dolomite. The corrected gamma ray log was used in all wells to determine the shale volume. Neutron-sonic log was used to calculate porosity at the reservoir unit while sonic log was employed to estimate the porosity at poor hole conditions and (non- reservoir units). Furthermore, the Indonesia model was used to calculate water saturation in Zubair reservoir and compared with the Archie model. Finally, Flow zone indicator method was used for permeability evaluation. The results show that the Zubair reservoir is primarily consists of sandstone, shale with compacted limestone, which was improved by the cuttings description report. The core porosity was validated in AMM-1, AMM-2, AMM-3and AMM-5 wells. Indonesia equation provides an optimum estimation in shaly sand zones since the Archie model takes the matrix conductive and the fluid conductivity into account. Four hydraulic flow units produced from reservoir quality index against normalized porosity index cross plot and obtained Four equations from porosity- permeability relationship of core data. The general interpretation presented that the most of hydrocarbons are located in depth (3332.8 m to 3415.8 m) which represents the best layer in Zubair reservoir, the properties of this layer in well AMM-1better than in well AMM-2. Finally, the layer from 3574.8 m to3638.3 m supposed to be water layer rather than hydrocarbon layer.

3D Geological Modeling for Characterizing the Bahariya Formation and Abu Roash G Dolomite Unit, Horus Field, North Western Desert, Egypt

The Horus field is considered one of the most important hydrocarbon producers within the Alamein basin, Western Desert of Egypt. This area was affected by different tectonic movements throughout geological history. The re-evaluation and characterization of the Horus area, especially its main reservoirs of Lower Bahariya, middle Bahariya, upper Bahariya, and AR/G Dolomite units, because of its low production of oil tend (only 1100 BBD). Despite this, the Alamein basin is large and very rich in hydrocarbon. This study depends on the interpretation of thirty 2D seismic lines in addition to open-hole logs in the form of Resistivity, SP, GR, Density, Neutron, and Sonic logs for the five studied wells in order to delineate the subsurface structure and reservoir petrophysical characteristics of the Horus field. The data is tried to the formation tops and seismic lines by using synthetic seismograms. The main surfaces were mapped to proceed with the further static modeling. The work flow of the 3D geological modeling in the Horus area for characterization of the Bahariya Formation and AR/G Dolomite Unit. The processes that were carried out during the construction of the geological structure in the study area respectively, fault modeling, pillar gridding, skeleton grid, horizon modeling, zonation, and layering, and then distributed the facies and petrophysical parameters (Vsh, Sw and Φe) in this model. The main objective of this study is to delineate the seismic phenomena for structural, petrophysical, and facies modelling of the Bahariya Formation (Lower, Middle, and Upper) and AR/G Dolomite unit. The depth structure contour map on top of the Bahariya formation and the AR/G Dolomite unit indicated that the Horus area affected by NW-SE and WNW-ESE faults related to the lower Cretaceous. The study discussed the possibility of new structural traps that benefit in increasing the production of the area. All the results were consistent and confirmed that the Bahariya Formation and AR/G Dolomite are excellent reservoirs. Integrating multidisciplinary methods of seismic interpretation, static modeling, property modeling and well log analysis to design 3D structural and property models, helped predict new exploratory promising areas and structural traps to increase in production and the reserves in the study area, also decreasing the uncertainty of hydrocarbon exploration.

Distal accumulation of leaked gas from deep overpressured zone：the case of the Yanan Sag, Qiongdongnan Basin, South China Sea

In the overpressured Yanan Sag of Qiongdongnan Basin, South China Sea, four structures contain varying gas volumes despite overall similarities in geological conditions. One notable difference, however, is their varying pressure characteristics. We investigated the nature and cause of the overpressure as well as its relation to natural gas migration-accumulation in the four structures. Well logs, drill-stem tests (DSTs), and mud weights, reveal two zones of overpressure in the YC21-1 and YC26-1 structures that contain no economic gas reservoirs. There is one zone of overpressure in the YC13-1 structure, whereas the YC13-4 structure is hydrostatically pressured. Cross-plot analysis of density and sonic logs indicates a mild to moderate overpressure section in the Neogene strata, interpreted as resulting from disequilibrium compaction and clay diagenesis.The Pliocene to Quaternary is considered to be a key period for strong overpressure formation in the Yanan Sag. Fast subsidence and burial may have induced intense gas generation by maturation and vertical compaction disequilibrium in the Oligocene strata of the central Yanan Sag. The resulting high pressure would have been transferred to the Oligocene reservoirs in the YC21-1 and YC26-1 structures in the slope belt. Fluid-inclusion homogenization temperature (Th) in combination with modeled burial curves indicates that gas filled the four structures during this period, suggesting that gas migration was associated with overpressure. Fluid-inclusion phase reflecting gas saturation and abnormal excursion of vitrinite reflectance (%Ro) suggest that leakage related to caprock fracturing resulted in gas accumulation failure in the high-pressure YC21-1 and YC26-1 structures. 13C depletion of methane in the YC13-1 and YC13-4 structures away from the sag center suggests that the current gases probably result from gas exsolution from formation waters. These gases are high-to over-mature, and thus were mainly derived from the deeper, central Yanan Sag rather than the local source rocks. Therefore, we infer that the gas leaked from the deep high-pressure zone in the sag center, then migrated in solution until a point at which PVT conditions would allow exsolution. Subsequently, the free gas would have migrated into the normally pressured reservoirs in the slope belts where it finally accumulated. Compared to the YC13-4 structure, the overlying Neogene mudstones in the YC13-1 structure are overpressured, which may serve to increase the seal capacity and explain the higher gas reserves in this area.

Natural fractures characterization by integration of FMI logs, well logs and core data: a case study from the Sarvak Formation (Iran)

Carbonate reservoirs in Iran are the most important and main sources of oil and gas production. Hydrocarbon flow rates from carbonate reservoirs heavily rely on the development of natural fractures. This study focuses on the role of natural fractures on reservoir quality considering the Sarvak carbonate reservoir (southwest Iran) as the second most important oil reservoir of Iran. To identify small-scale fractures around the borehole walls, cores description and image logs were utilized. Due to high cost of coring, lack of orientation and low core recovery in fractured zones indirect methods based on image logs and conventional well logs were exploited for fracture characterizations. For this purpose, a complete set of well data including image logs (FMI), well-log-derived porosity and permeability data together with petrophysical logs were employed. Interpretation of image logs allows different types of natural structures such as open, vuggy, partly-filled and filled fractures, bedding planes and stylolites to be identified. Comparisons between the petrophysical-log and image-log interpretations provide useful relationships with reservoir characteristics. Neutron and sonic logs show a direct relationship with fracture porosity, while the density log displays an inverse correlation with fracture porosity. Neutron-density and neutron-sonic cross-plots show that the dominant lithology of the studied well is limestone with minor fractions of dolomite and shale. Total porosity ranges from 2 to 30%, while the contribution of secondary porosity, on average, is below 3%. Relationships between fracture-frequency diagrams and reservoir permeability show that high permeability zones are well correlated with the high frequencies of open and vuggy fractures and zones that have flowed oil and associated gas in production tests. Natural fracture characterization based on systematic and integrated interpretations of image logs and petrophysical data can play an important role in optimizing field development, resource recovery and production from the Sarvak reservoir. Once calibrated, this method also offers potential as an exploration tool.

Inversion of seismic data to modeling the Interval Velocity in an Oilfield of SW Iran

Seismic velocity is considered the best attribute related to formation pressure changes. Integrating seismic attributes and well-logging data through seismic inversion predicts the reservoir characteristics across the field with the highest accuracy. This study especially presents seismic velocity for the whole south Azadegan Field in SW Iran for carbonate formations. The considered dataset includes 3D seismic data, vertical seismic profiling (VSP), logging data of 23 wells, and geological information. Here, we estimated the interval velocity using post-stack migration velocity, seismic inversion, and the relationship between the acoustic impedance (AI) model and the sonic log to predict formation pressure. As a result, the correlation coefficient of 0.71 and a high inversion accuracy (8.76% relative error) is concluded. The actual and predicted P-wave (Vp) correlation coefficient is calculated as 0.74 and all sevens as 0.79 using an AI seismic attribute. Thus, the estimated Vp agrees with the original well-log values. Inverted AI cubes in the deeper formations of the field are about 8000-15000 [(m/s)*(g/cm3)], which could be referred to as calcareous formations. The correlation of the Vp cube resulting from the Sequential Gaussian simulation (SGS) considering co-kriging with the AI, with the initial velocity cube using the inverse distance weighted (IDW) method being 0.54 is more than the same method applied with interval migration velocity trend in co-kriging. The anisotropy of the final Vp cube for the vertical variogram range is 96m, and for major and minor directions is 11850 m.

NMR log response prediction from conventional petrophysical logs with XGBoost-PSO framework

A combined approach that exploits both the eXtreme Gradient Boosting (XGBoost) method and the Particle Swarm Optimization (PSO) method was used here to predict the nuclear magnetic resonance (NMR) log parameters such as porosity and permeability from field measurements. Data obtained by NMR are extremely critical for modeling the reservoir behavior and are among the most vital inputs for reservoir simulations. Therefore, developing an intelligent framework that can accurately predict NMR logging response by using conventional, low-cost logging data can be a valuable tool for field development. A number of conventional well logs, such as neutron, density, sonic, caliper, gamma-ray, and resistivity logs, recorded from sixteen wells in an offshore oilfield in Persian Gulf were used in the XGBoost-PSO framework to predict NMR log response. The outputs are the free fluid porosity (CMFF), bound fluid porosity (BFV), permeability (KTIM), and total porosity (TCMR). Based on the results, in terms of prediction accuracy, comparing correlation coefficients, the XGBoost-PSO model performs in the range of 88.5–91.4%. Moreover, the application of PSO in hyperparameter optimization of predicted parameters confirmed at least five percent improvement. Overall, we were able to demonstrate that ordinary conventional logging data can be utilized to obtain more advanced NMR data without performing expensive, time-consuming, and high-risk logging operations to decrease operational costs without compromising the benefits.

Derivation of rock's geomechanical parameters while drilling by combining surface drilling data, gamma ray data, and machine learning techniques in carbonate formations

This work presents a field application of an effective and reliable methodology for geomechanical parameters evaluation, using surface logging drilling data (rate of penetration, torque, weight on bit, stand pipe pressure, rotation per minute, flow rates) and well log data (sonic log, bulk density log, gamma ray log) to feed a model characterised by the combination of different machine learning algorithms (multiple linear regression, support vector regression, random forest, artificial neural network, and XGBoost). To expand the range of application to those cases where the downhole tools are not technically feasible or economically viable, a flexible workflow has been developed to derive a Synthetic Gamma Ray (SGR) from X-ray Fluorescence (XRF) analysis performed on cuttings. The methodology, applied to a dataset of 11 wells drilled in the same geological units but in different fields in Kuwait, proves its successful use to derive several geomechanical parameters, among which the results associated with Young’s Modulus, density, and Poisson’s Ratios are here presented.

A New Method for 3D Detection of Defects in Diaphragm Walls during Deep Excavations Using Cross-Hole Sonic Logging and Ground-Penetrating Radar

With the development of deep underground space, there is an ever-growing demand for the excavation of deep foundations in the urban zone. The diaphragm wall is the most commonly used retaining and waterproof structure. Therefore, the quality of the diaphragm wall plays an essential role in the environmental impact and security risk control of deep foundation excavation. Consequently, it is required to develop practical ways to detect defects in diaphragm walls. It is critical to localize defects before excavation and characterize them in detail for proper countermeasures. Unfortunately, up to now, the traditional detection methods are not yet available for professional use. This paper presents a contribution to filling this gap based on cross-hole sonic logging (CSL) and ground-penetrating radar (GPR). First, CSL is carried out prior to excavation through detection tubes preinstalled in the wall. Second, Bayesian inversion is used to obtain a high-quality two-dimensional (2D) visualization of the defects, and the depth and width can be obtained before excavation. Third, GPR is applied to precise detection when excavating to the depth of the defect. Finally, by employing an advanced bifrequency back-projection method, the correlation between two domain frequency radar data is used to obtain the three-dimensional (3D) characteristics of the defects. The proposed method was used at a 40-m level of deep excavation in Shanghai, China, and allowed engineers to determine the location and 3D characteristics of defects. An identified analysis of the defects with this method showed a reasonably good match with manual observation after excavation.

Prediction of Well Logs Data and Estimation of Petrophysical Parameters of Mishrif Formation, Nasiriya Field, South of Iraq Using Artificial Neural Network (ANN)

Petrophysical properties including volume of shale, porosity and water saturation are significance parameters for petroleum companies in evaluating the reservoirs and determining the hydrocarbon zones. These can be achieved through conventional petrophysical calculations from the well logs data such as gamma ray, sonic, neutron, density and deep resistivity. The well logging operations of the targeted limestone Mishrif reservoirs in Ns-X Well, Nasiriya Oilfield, south of Iraq could not be done due to some problems related to the well condition. The gamma ray log was the only recorded log through the cased borehole. Therefore, evaluating the reservoirs and estimating the perforation zones has not performed and the drilled well was abandoned. This paper presents a solution to estimate the missing open-hole logs of Mishrif Formation including sonic, neutron, density and deep resistivity using supervised Artificial Neural Network (ANN) in Petrel software (2016.2). Furthermore, the original gamma-ray log along with the predicted logs data from ANN models were processed, and the petrophysical properties including volume of shale, effective porosity and water saturation were calculated to determine the hydrocarbon zones. The ANN Mishrif Formation models recorded coefficient of determination (R2) of 0.65, 0.77, 0.82, and 0.04 between the predicted and the tested logs data with total correlations of 0.67, 0.91, 0.84 and 0.57 for sonic, neutron, density, and resistivity logs respectively. The best possible hydrocarbon-bearing zone ranges from the depth of about 1980-2030 m in the mB1unit. The ANN provides a good accuracy and data matching in clean and non-heterogeneous formations compared to those with higher heterogeneity that contain more than one type of lithology. The Ns-X Well can, therefore, be linked to the development plans of the Nasiriya Field instead of neglect it.

Evaluation and Economics of Shale Gas Reserves in the Flysch-Eocene Formation of the Jaca Basin

The new international outlook for the gas sector suggests evaluating exploitable reserves in previously unconsidered areas including hydraulic fracturing technology. In order to estimate the amount of gas in the Jaca Flysch formation, the analysis of geological and geophysical logs and the volumetric method have been used. It has been taking into account the part of the formation likely to contain gas, the porosity (2.65%) calculated from sonic logs with Wyllie’s equation, the water saturation (35.3%) with Archie’s formula, and the initial gas formation volume factor (Bgi), estimated with MHA-P3 software with the reservoir pressure/temperature data 3600 psi/90 °C. The economic analysis of each well has been carried out based on three options, without stimulation, with 50% and 100% stimulation by fracking, and five possible construction costs (7.5–15 MM€). The impact of the use of the fracking technology on the production of the well is about 48%. The production rate and the economic impact that its exploitation would have on the domestic demand for natural gas has been analyzed, resulting in a significant contribution to the national energy mix of between 10–20% of consumption for several years.

Integrating facies analysis and geostatistical methods in an onshore oil field using petrophysical groups

Reservoir facies studies are of great importance in different stages of exploration and development of hydrocarbon fields. We have aimed to generate a reservoir facies model for the Asmari Formation in an onshore oil field located in southwest Iran. Input data for electrofacies (EF) clustering algorithms are used, which include gamma-ray (GR), density (RHOB), porosity, and sonic logs from four wells. We obtain the petrophysical group (PG) and EF class using core drill data (mercury injection capillary pressure) and well-logs analysis. The integration of PGs and log EF significantly decreases the uncertainty in reservoir modeling, which alternatively enhances field development decisions. We compare the multiresolution graph-based clustering (MRGC) and k-means clustering methods. EF clustering results find nine EF classes. We delineate high-quality reservoirs based on lower GR, RHOB, and high-porosity logs. Next, we use the clustering results in the static reservoir modeling process, using the sequential index simulation and indicator kriging methods. The comparison between the facies obtained models and existing drilling core data finds that the absolute percentage error of the MRGC algorithm is less than that of the k-means algorithm. The results obtained by this study can provide useful information for the development of hydrocarbon exploration plans in the studied oil field.

Unsupervised Machine Learning Techniques for Improving Reservoir Interpretation Using Walkaway VSP and Sonic Log Data

In this paper, we present a detailed analysis of the possibility of using unsupervised machine learning techniques for reservoir interpretation based on the parameters obtained from geophysical measurements that are related to the elastic properties of rocks. Four different clustering algorithms were compared, including balanced iterative reducing and clustering using hierarchies, the Gaussian mixture model, k-means, and spectral clustering. Measurements with different vertical resolutions were used. The first set of input parameters was obtained from the walkaway VSP survey. The second one was acquired in the well using a full-wave sonic tool. Apart from the study of algorithms used for clustering, two data pre-processing paths were analyzed in the context of matching the vertical resolution of both methods. The validation of the final results was carried out using a lithological identification of the medium based on an analysis of the drill core. The measurements were performed in Silurian rocks (claystone, mudstone, marly claystone) lying under an overburdened Zechstein formation (salt and anhydrite). This formation is known for high attenuating seismic signal properties. The presented study shows results from the first and only multilevel walkaway VSP acquisition in Poland.

Study on calculation of transversely isotropic dynamic rock mechanical parameters and conversion model between dynamic parameters and static parameters

The shale oil reservoirs in the Jimsar Sag are strongly heterogeneous. Therefore, it is of practical significance to relate the dynamic elastic stiffness to the static elastic stiffness under the assumption of transverse isotropy. The acquisition of stiffness parameters depends on lab measurements or Sonic Scanner logging. Aiming at the problem that the lab measurements results are limited and discontinuous, the acquisition of special logging data is difficult in the well site, a method using only the conventional well-log data to predict the dynamic elastic stiffnesses of shale is proposed. Inspired by ultrasonic experimental test method, the study simplified the types of tested waves and complemented missing datas. According to the experimental proof, we concluded that: (1) Under the assumption of transverse isotropy, using simplified Thmosen model and velocity conversion relationship can accurately calculate the P-wave and S-wave velocities in the 45° angle direction. (2) Compared with the conventional isotropic algorithm, specify this algorithm can better reflect real mechanical conditions of the formation, and better characterize the variation of mechanical parameters with depth. (3) Effective conversion models between dynamic elastic modulus and static elastic modulus in vertical and horizontal directions were obtained in some areas of Jimsar.

Identification of Hydrocarbon Zones and Chimneys Using Seismic Attributes Analysis at Woda Oil Field, Western Offshore Niger Delta

This research investigated hydrocarbon zones and chimneys using seismic attributes analysis in Woda Oil Field, Western offshore Niger Delta. Seismic attributes are powerful tools in monitoring and predicting hydrocarbon zones. Detailed application of seismic attributes on the Woda seismic data aided in the extraction of important information about the geologic features on seismic profiles. Materials used in this research include well logs, seismic data and 3D Post Stack Depth Migration (PSDM) seismic volume. Methods used were seismic attribute analysis and well log interpretation. The reservoirs of interest were identified and analyzed using well log data based on gamma ray, resistivity, and Vp sonic log response. Seismic attributes such as chaos, root mean square velocity, similarity and reflection intensity were quality controlled, enhanced, and generated which assisted in identifying chimneys and hydrocarbon zones. The majority of the chimneys in this research may have nucleated in the lower part of the faulting system below the partially permeable portion of the fault planes and across a regional partially permeable barrier as revealed by thin fault likelihood attribute. Gas expulsion along the lower portion of the complex faulting system perhaps, may have preconfigured the spatial organization of the chimneys. Pockmarks formation above the chimneys as revealed by the sweetness attribute may have inherited the same linear planiform geometry, and both structures recorded the timing of hydrocarbon zones and gas expulsion within the Woda Oil Field.

Beyond conventional approach: hybrid supervised learning and feature selection algorithms for prediction sonic logs - a study in a tight gas sand, North of Oman

Beyond conventional approach: hybrid supervised learning and feature selection algorithms for prediction sonic logs - a study in a tight gas sand, North of Oman

Beyond conventional approach: hybrid supervised learning and feature selection algorithms for prediction sonic logs - a study in a tight gas sand, North of Oman

Beyond conventional approach: hybrid supervised learning and feature selection algorithms for prediction sonic logs - a study in a tight gas sand, North of Oman

The assessment of rock drillability from elastic and petrophysical parameters

ABSTRACT Rock strength is an essential and effective property in the rock drilling, excavation, and cost evaluation. This work aims to examine a practical approach to evaluate the geomechanical properties that control rock drillability, such as uniaxial compressive strength (UCS) by utilising some petrophysical parameters (porosity and bulk density) and elastic properties (Young’s modulus, bulk modulus, and slowness). To achieve this aim, the study was conducted on some Jurassic rock samples that were cored from different localities in Gebel El-Maghara, North Sinai, Egypt. The uniaxial compressive strength (UCS) was calculated from the measured porosity of 28 sandstone and 89 carbonate plug samples. Empirical equations that relate the uniaxial compressive strength of sandstone and carbonate rocks to physical properties and elastic properties are represented. The physical and elastic parameters that were measured from logging data (sonic, density, neutron, and gamma-ray logs) can be utilised in other future studies to predict the strength of the rock by using these empirical equations that were inferred in this study. The comparison between the relationships of calculated results of UCS in this study with the relationships of laboratory rock strength of different types of sedimentary rocks collected from different places around the worldfrom the previous studies shows high compatibility. The estimated equations from regression analysis of sandstone are more recommended than carbonate.