The Cambrian-Ordovician and Upper Cretaceous formations, which are the main oil-producing formations in the central Sirte Basin, are structurally complex. The lateral and vertical heterogeneity of the reservoir formations is not well-understood, which negatively affects the performance of the reservoirs. We constructed efficient full-field static models that incorporate the lateral and vertical variation of those reservoir formations by integrating geologic and geophysical data. We determined lithology and reservoir properties by selecting appropriate petrophysical techniques that suit the available well data and (...) overcome issues with unreliable well-log measurements. In the process of building structural models, defining and mapping the base of the Cambrian-Ordovician Gargaf Formation was very challenging because wells did not penetrate the basal formation, and the quality of the seismic data decreases with depth. Therefore, we applied techniques of adding isochore maps of the overlying Upper Cretaceous of the Bahi and Waha Formations to map basal contact and determine the thickness of the Gargaf Formation for the first time in the area. The constructed isochore maps showed the thickness variation and the distributions of the Bahi and Waha Formations and explained the influence of Gargaf paleotopography and faults on them. The fault models combined with facies and property models suggested an interconnection among the three main reservoirs. They also indicated that the quality of the Waha reservoir enhances as the lithology varies from limestones to calcareous sandstones, whereas the quality of the Gargaf reservoir was primarily controlled by fractures. The total estimate of the original oil in place with the largest contribution of hydrocarbon volume from the Waha Formation was [Formula: see text] stock tank barrel. The created model with a fine-scale geocellular covering an area of [Formula: see text] is unique to the study area and it can be updated and refined at any time with new data production and drilling activities. (shrink)

Seismic imaging of the shallow subsurface can be very challenging when reflections are absent and the data are dominated by ground roll. I analyzed the transmission coda to produce fine-scale, interpretable vertical and horizontal component seismic velocity models using full-waveform inversion. Application of FWI is tested through imaging two buried targets. The first target is a pair of well-documented utility pipes with known diameters and burial depths. The second target is a poorly documented former location of the pipe, which is (...) now a backfilled void. Data are acquired along a 23 m 2D profile using a static array with single-component vertical and horizontal geophones. Our results indicate considerable velocity updates in the [Formula: see text] and [Formula: see text] models across the pipes and backfill. The pipes appear as negative velocity updates in the final inverted [Formula: see text] and [Formula: see text] models, whereas the backfilled area represents negative and positive velocity updates in the [Formula: see text] and [Formula: see text] models, respectively. Variations of the polarities in the inverted models across the backfill can be indicative of the medium, which respond differently to the vertical and horizontal component seismic waves. The attenuation models show a general decreasing trend with increasing depth. Therefore, simultaneous applications of vertical and horizontal component seismic velocity modeling can be an effective tool to understand the subsurface medium in near-surface characterization. (shrink)

Understanding natural fracture systems is key for tight carbonate plays, in which production is dependent on secondary interconnected porosity networks. Locating geographic areas and stratigraphic sections with high natural fracture density and optimizing well locations and perforations to connect these fractures can enhance well performance and asset value. There is substantial production variation in the Cretaceous stacked carbonate play in East Texas, despite similarities in well completion and perforated intervals. Petrophysical property models did not explain the significant variation in well (...) production; therefore, we have developed a multidisciplinary workflow combining seismic and log data with the goal of identifying faulting and natural fractures and understanding their effect on production. We used seismic discontinuity to map faults as the main indicator of presence of fractures. We calibrated triple combo logs with an image log to generate an indicator curve to identify natural fractures. The fracture indicator curve provided a good prediction of where natural fractures may occur, and discontinuity maps revealed a good correlation to well production. Furthermore, we concluded that drilling too closely to large faults negatively impacted production and correlated with increased water production. The workflow developed here can be used to optimize well placement in the stacked carbonate play of Madison County, Texas, and it can be applied to other fractured carbonate reservoirs. (shrink)

We have developed a simulation of the electromagnetic response and its joint interpretation with fracking monitoring simulation during hydraulic fracturing in an unconventional reservoir. A multiphysics workflow is presented, using a criterion based on a breakdown pressure to generate and propagate the hydraulic fracturing, where the pressure response and EM response were jointly constructed. The approximate solution of Maxwell equations was obtained using a mixed finite-element method combined with a leapfrog time-stepping procedure. The spatial discretization of the Maxwell’s equations is (...) achieved using the mixed finite-element spaces of Nedelec, in which the electrical fields have a continuous tangential component across the edges of the computational mesh. Leapfrog time stepping was used for the time discretization, so that the fully discrete sequence is first solving for the electric field using preconditioned conjugate gradient iteration and then solving for the magnetic field. A stability analysis of this FEM method is provided. The results indicate that the EM response might be sensitive enough to be monitored and the magnetic field correlates better with the saturation distribution than the electric field. Furthermore, due to its relation to water saturation and effective connectivity, it is shown that EM monitoring yields additional information to determine the stimulated reservoir volume. An error analysis of estimations from EM and the actual saturation size indicates that the petrophysical assumption is perhaps the most sensitive part of this study. (shrink)

Lower Triassic Feixianguan oolithic shoal complexes are widely developed in the northwestern Sichuan Basin, southwest China, where they host large natural gas reserves. To understand their development and the factors that controlled their deposition, we have used observations and interpretations of outcrops, cores, thin sections, well-log data, and seismic data to characterize the geologic and geophysical properties of the oolithic shoals of the Lower Triassic Feixianguan Formation in the Jiange area, northwestern Sichuan Basin. The oolithic shoals of the Feixianguan Formation (...) are composed of locally dolomitized oolithic grainstones or packstones deposited in a semirestricted platform environment. With a thickness of more than 50 m, oolithic shoals mainly occur in the Fei 2 Member within the southeastern Jiange area. The results indicate that the shoals mainly lie above tectonic uplifts and surrounding microtopographic highs. Furthermore, the prograding clinoforms and changes in accommodation space caused by sea-level fall influence the thickness of oolithic shoal deposits, and constrain their development in highstand systems tracts, resulting in their migration coinciding with the trend of clinoform progradation. We concluded that the development of oolithic shoals in the Jiange area may be controlled by two major factors: the influence of paleotopography governed by the syndepositional faults on the accumulation of oolithic shoals and the role of sea-level change in the migration of oolithic shoals. (shrink)

The quantitative prediction of the mineral composition, porosity, and kerogen content of shales is significant for the evaluation of shale oil and gas potential and the hydraulic fracturing process. We have developed a new method for the shale’s components prediction by combining the back-propagation neural network and an improved [Formula: see text] method based on conventional logs. First, we constructed and calibrated the shale fraction model according to the volume of the minerals, kerogen, and porosity determined through laboratory analyses. Subsequently, (...) we calculated the kerogen volume by the combination of the improved [Formula: see text] technique and the conversion equation between the kerogen volume and the organic carbon content. Finally, the BP neural network was trained with the input parameters of the kerogen volume and the sensitive logs, and the output parameters of the mineral volume and porosity. We used the cross validation method to optimize the structural parameters of the BP neural network. The SCP-[Formula: see text] method, which is a nonlinear technique, takes into consideration the influence of the organic carbon of the residual oil on the calculation of the kerogen volume. We successfully implemented the SCP-[Formula: see text] method to evaluate the shale components of well Shen 352 in the Damintun Sag, China. The evaluation results of the SCP-[Formula: see text] method are in good agreement with the measured core sample properties and mineral composition derived from Schlumberger elemental-capture spectroscopy logs, confirming the accuracy and reliability of the SCP-[Formula: see text] method in predicting the mineral composition, porosity, and kerogen content in shale. (shrink)

In seismic mapping of reservoirs, it is usually difficult to identify a single layer in a thin interbed formation. The main reason for this is interference of adjacent layers in the thin beds. We have developed a slice method basis spectral decomposition workflow to decrease this interference rely on the good vertical resolution of the thin layers, which is not always achievable. To overcome this, we have developed two frequencies at which the thin-bed response is weakest at a fixed time. (...) These are the low minimum interference and high minimum interference frequencies. The LMI frequency is useful for thin-bed detection when the thin bed cannot be resolved vertically in the seismic profile. The LMI frequency is usually less than the dominant frequency. However, the thin bed can still be identified on the seismic slice at this frequency. In practice, the LMI frequency can be estimated from the time-frequency spectrum and used in spectral decomposition using wavelet transformation to generate the amplitude slices for various frequencies. The amplitude slicing method was verified by case studies using synthetic and real data from a seismic exploration site in the Junggar Basin, China. The results indicate that this methodology is feasible and effective in identifying oil reservoirs in the thin interbeds strata. (shrink)

We have conducted seismic-attribute analysis at the Serbin field — in an area straddling Lee, Fayette, and Bastrop Counties and covering approximately [Formula: see text] — using new, reprocessed, 3D seismic data to provide additional understanding of depositional environments and better predict the distribution of hydrocarbon sweet spots. We converted the 3D seismic volume into a log-lithology volume and integrated core data to examine the distribution of lithology and interpret depositional environments. By conducting multiattribute analysis, we predicted resistivity volume and (...) generated a resistivity map to identify hydrocarbon sweet spots. Our results show that reservoir sandstones in the Serbin field are storm-dominated, shelf-sand deposits. Although individual sandstone beds are lenticular and discontinuous, they collectively constitute a sheet-like geometry, trending northeast to southwest. On the basis of resistivity maps and rock property versus seismic-amplitude crossplots, we differentiated reservoirs in the lower Taylor Formation into two zones: a northwest, high-resistivity, high-acoustic impedance zone and a southeast, low-resistivity, low-acoustic impedance zone. The results also indicated that hydrocarbon sweet spots in the Serbin field are characterized by high resistivity and high impedance. Furthermore, the log-lithology method, although fast and effective, is limited because it cannot take into account sandstone zones having low acoustic impedance. (shrink)

The eastern part of Tazhong area in the Tarim Basin consists of three sets of vertical strike-slip faults oriented in north–northeast, east–northeast, and west–northwest directions that cut the strata from Cambrian to Carboniferous. The fault belts indicate significant horizon upwarp and downwarp deformations and variations in their stratigraphic thickness on seismic profiles. Through detailed interpretation of the 3D seismic data, we consider that these phenomena reflect the different stress properties and active stages of the faults. The horizon upwarp and downwarp (...) within the fault belts correlated respectively to the decrease and increase in stratigraphic thickness within the fault belts in comparison to the coeval counterpart of the bilateral fault blocks. For the same fault, different stratigraphic intervals express different types of horizon deformation and thickness changes. The horizon downwarp and the contemporaneous stratigraphic thickening inside the fault belts suggest the transtensional actions of the fault. The horizon upwarp and the contemporaneous thinning within the fault belts suggest transpressional actions of the fault. Based on this, we inferred the active periods of the three sets of strike-slip faults. The north–northeast-striking faults were formed in the late Ordovician Sangtamu Formation. This set of faults experienced four stages, i.e., sinistral transpression, sinistral transtension, static, and transtension. The east–northeast and west–northwest-striking faults initiated in the mid-Cambrian period as coupled transtension. Activity ceased in the west–northwest faults after the mid-Cambrian and in the east–northeast faults during the late Ordovician. The three sets of strike-slip faults all affect the formation of the hydrothermal dissolution reservoirs that are distributed in the Ordovician carbonate rocks. (shrink)

The study of sand bodies and coalbeds that formed during strong events is conducive to understand the relationship between source rocks and reservoirs. Two sets of Late Paleozoic coal-bearing sequences including the Late Carboniferous Taiyuan Formation and Early Permian Shanxi Formation, with an accumulated thickness of more than a half wavelength, were deposited in the Hangjinqi region on the northern margin of the Ordos Basin. These strata appear as two peaks and two troughs, three peaks and three troughs in the (...) 3D seismic data. We analyzed this coal-bearing seismic response through a combination of well-data statistical analysis, the establishment of forward modeling, and the creation of crossplots. The coal-seam thicknesses of the Taiyuan and Shanxi Formations and the spacing between the two sets of coal indicate the major roles in the merging and bifurcation of events. The formation of three peaks and three troughs requires that the thicknesses of the two sets of coal are greater than 2 m. The spacing between the two sets of coal must also exceed 10 m with a detectable lateral extension, which would otherwise generate two peaks and two troughs. The two peaks and two troughs indicate a combined relationship between the thin sandstones at the bottom of the Shanxi Formation and the thick coalbeds in the Taiyuan and Shanxi Formations. The three peaks and three troughs suggest a combined relationship between the thick sandstones at the bottom of the Shanxi Formation and the thin coalbeds in the Taiyuan and Shanxi Formations. The drilling results clarified that the well situated at the two peaks and two troughs regions is accompanied by higher gas productivity, revealing that the coal-seam thickness has a significant influence on gas accumulation. The presence of two peaks and two troughs indicates favorability for natural gas exploration. (shrink)

A 3D seismic image contains structural and stratigraphic features such as reflections, faults, and channels. When smoothing such an image, we want to enhance all of these features so that they are easier to interpret. Most smoothing methods aim to enhance reflections but may blur faults and channels in the image. A few methods smooth seismic reflections while preserving faults and channel boundaries. However, it has not well-discussed to smooth simultaneously along the seismic reflections and channels, which are linear features (...) apparent within dipping reflections. In addition, to interpret faults and channels, extra steps are required to compute attributes or mappings of faults and channels from a seismic image. Such fault and channel attributes are often sensitive to noise because they are typically computed as discontinuities of seismic reflections. In this paper, we have developed methods to simultaneously enhance seismic reflections, faults, and channels while obtaining mappings of the faults and channels. In these methods, we first estimate the orientations of the reflections, faults, and channels directly in a seismic image. We then use the estimated orientations to control the smoothing directions in an efficient iterative diffusion scheme to smooth a seismic image along the reflections and channels. In this iterative scheme, we also efficiently compute mappings of faults and channels, which are used to control smoothing extents in the diffusion to stop smoothing across them. This diffusion scheme iteratively smooths a seismic image along reflections and channels while updating the mappings of faults and channels. By doing this, we will finally obtain an enhanced seismic image and cleaned mappings of faults and channels. We have examined the methods using 2D and 3D real seismic images. (shrink)

Blending of different frequency components of seismic traces is a common way to estimate the relative time thickness of the formation. Red, blue, and green color blending is one of the most popular blending models in analyzing multiple seismic attributes. Geologists and geophysicist interpreters typically associate low-frequency components with a red color, medium-frequency components with a green color, and high-frequency components with a blue color for the thickness estimation of thin beds using frequency components. However, we found that the same (...) result of RGB blending may come from different sets of three frequency components. As a result, the same blended color may correspond to several different time thicknesses. It is also very difficult to interpret the corresponding thickness of the blended colors such as white and yellow. To avoid the ambiguity of time-thickness estimation using RGB blending, we have estimated the time thickness of the thin beds using all of the frequency components in a user-defined frequency band instead of only three frequency components. Our workflow begins with the normal seismic spectral decomposition. Considering that the different reflectivity pairs with a different time thickness have a different amplitude spectrum, we then use the self-organizing map to cluster the decomposed amplitude spectra of seismic traces. We finally assign each cluster with a relative thickness by comparing the clustered results with well logs. (shrink)

Porosity is a fundamental property that characterizes the storage capability of fluid and gas-bearing formations in a reservoir. An accurate porosity value can be measured from core samples in the laboratory; however, core analysis is expensive and time consuming. Well-log data can be used to calculate porosity, but the availability of log suites is often limited in mature fields. Therefore, robust porosity prediction requires integration of core-measured porosity with available well-log suites to control for changes in lithology and fluid content. (...) A support vector machine model with mixed kernel function is used to construct the relationship between limited conventional well-log suites and sparse core data. Porosity is the desired output, and two conventional well-log responses and three well-log-derived parameters are input parameters. A global stochastic searching algorithm, particle swarm optimization, is applied to improve the efficiency of locating the appropriate values of five control parameters in MKF-SVM model. The results of SVM with different traditional kernel functions were compared, and the MKF-SVM model provided an improvement over the traditional SVM model. To confirm the advantage of the hybrid PSO-MKF-SVM model, the results from three models: radial basis function -based least-squares SVM, multilayer perceptron artificial neural network, and RBF ANN, are compared with the result of the hybrid PSO-MKF-SVM model. The results indicate that the hybrid PSO-MKF-SVM model improves porosity prediction with the highest correlation coefficient, the highest coefficient of determination, the lowest root-mean-square error, average absolute error value, and maximum absolute error. (shrink)