Thinly Bedded Reservoirs Research Articles

Petrography and Diagenesis of Thin-Bed Reservoirs from the Eastern Folded Belt of Bangladesh

The main purpose of the study is to identify the thin-bed reservoirs of the Eastern Folded Belt (Sylhet and Bandarban) and characterize them with diligence. A detailed qualitative and quantitative analysis has been carried out. It is based on thin-section petrographic analyses of sandstone samples. These samples are from the reservoir horizons of the Sylhet region and Bandarban region fields. The purpose of this analysis is to characterize the textural and mineralogical properties. Additionally, it aims to evaluate the post-depositional diagenetic changes. The results obtained from the field and laboratory analysis are studied extensively to characterize the thin-bed reservoirs. Samples from the Sylhet area are medium-coarse-grained, fairly sorted, tight packing, submature-mature sublithic characteristics. Contrarily, samples from the Bandarban region are mature-submature sublithic arenites, which are fine-medium-grained, moderately well-sorted, and moderately loosely packed. Despite the similarity of the detrital elements (quartz, feldspar, lithic grains, mica, etc.) in the two areas, silica cementation is more frequent in Sylhet region samples than early carbonate cementation in Bandarban region samples. Comparatively speaking, the sediments in the Sylhet region are more compact than those in the Bandarban region. The most important outcome of this study is that the thin bed of the unconventional reservoir and the conventional reservoir are in close proximity. The Thin-bed reservoir units of the Eastern Folded Belt are found to be medium to fine-grained and well sorted, with frequent alteration of sand-shale with the prevalence of parallel bedded sandstone. Average porosity is 4% to 12%, and pore spaces are interconnected. So, the permeability rate is good enough to flow the hydrocarbon through these pore spaces. Most importantly, the thin bed and tight reservoir (average porosity 4% to 12%, but pore spaces are not interconnected) are not more prominent than 1 meter or 2 meters. Subsequently, though the vertical thickness is not so high, they keep up a momentous tirelessness of horizontal progression. On the contrary, at whatever point it comes to a conventional reservoir, the vertical thickness is higher than that of the unconventional reservoir. But their lateral persistence is not as long as unconventional ones.

Seismic forward modeling for investigating and interpreting thin beds in a carbonate reservoir in SW Iran

High-frequency contents of reflections are essential in the investigation and interpretation of thin-bed reservoirs. These beds can be even more complicated in carbonate rocks, as pore geometries influence final seismic responses. To address these complexities, we propose a seismic forward modeling workflow to investigate several thin-bed reservoirs in a carbonate oilfield with variable pore geometries. The new workflow enhances the existing forward models for the investigation of thin beds by integrating seismic petrophysics, geological model building, and 2D finite-difference elastic modeling. We used seismic petrophysics to ensure the consistency between petrophysical well logs and seismic data using rock physics modeling. Then, we introduced a new high-resolution workflow for velocity modeling to build a reliable geological model. Finally, the 2D finite-difference elastic modeling is employed to generate synthetic traces based on our geological model to obtain seismic responses for the existing thin-bed reservoirs. The forward models used in this study are a powerful tool for investigating thin layers because they enable high-resolution investigation of the given geological model in distinguishing lateral and vertical lithofacies changes. The new velocity modeling workflow, implemented in this research, is more reliable and effective than the conventional velocity property modeling approaches, which resulted in synthetic seismic sections with increased lateral and vertical resolutions and enhanced data from a thin bed. The main features of this workflow are the incorporation of well-log data into geological model building, combining the high-resolution data of horizontal seismic stacking velocity with vertical well logging, and the incorporation of a residual model to improve the seismic stacking velocity. We produced a more coherent section resembling the acquired 3D seismic data by applying the proposed workflow to data from an oil carbonate reservoir in the Fahliyan Formation within the Abadan Plain in SW Iran. It is concluded that the higher frequency synthetic sections from the proposed workflow can assist in resolving the seismic interpretation challenges. By applying the proposed workflow to the current data set, four thin-bed carbonate reservoirs were investigated with corresponding thicknesses of approximately 25, and 17 m at peak frequencies of 60, and 90 Hz, respectively.

A prestack seismic inversion method constrained by facies-controlled sedimentary structural features

The inversion of thin-bed reservoirs using seismic data is important for precise reservoir prediction. Most of the current thin-bed reservoir inversion methods are constrained by facies or sedimentary characteristics in reservoirs. The accuracy of the sedimentary characteristics severely affects the precision of the inversion results. There are differences in sedimentary patterns among different facies, but the same facies have similar sedimentary characteristics, and the similarity brings the sparsity of sedimentary structure within a facies. Thus, various representations should be used to describe the differences in the sedimentary patterns between facies. After analyzing the sparse representation (SR) patterns for different facies, a prestack seismic inversion method constrained by facies-controlled sedimentary structural features is developed. Our method first uses seismic attributes that provide rich details of seismic features to divide facies. Then, the sedimentary structural features within each facies are extracted. The inversion results are represented by structural features in the corresponding facies. We have used the represented results as the initial value of the inversion to iterate. Using this iterative inversion framework, we obtain results that are consistent with the sedimentary features of each facies. The representation of reservoir parameters by different SR patterns can avoid the mixing of sedimentary structural features in different facies. Synthetic and field examples are used to verify the effectiveness of our method. The method obtains inversion results that are consistent with seismic data and the distribution of thin-bed in well logs. Therefore, the method can be successfully applied to thin-bed sandstone reservoirs.

Seismic driven reservoir classification using advanced machine learning algorithms: A case study from the Lower Ranikot/Khadro sandstone gas reservoir, Kirthar Fold Belt, Lower Indus Basin, Pakistan

Reservoir characterization of thin sand bed reservoirs has been a challenge for petroleum explorers across the globe. In this study, we have studied the heterogeneous Paleocene sandstone gas reservoir of Lower Ranikot/Khadro, Kirthar Fold Belt, Lower Indus Basin, Pakistan. The studied reservoir is par below seismic resolution, with an average thickness that varies from 4 to 7 m at places and has provided a good amount of prosecution in some producing wells. The solution to the above challenges has been put forth where an integrated approach of seismic attributes, petrophysical properties, well logs, and facies data sets are combined with advanced machine learning algorithms to get better resolution for the studied thin-bedded sandstone resource. In addition, the thin heterogeneous sands of the Ranikot/Khadro Formation were characterized by predicting the elastic properties of the reservoir and classifying the facies distribution of hydrocarbon-bearing sands within the Zamzama Gas Field. Several machine learning (ML) algorithms were chosen and implemented on pre-stack seismic data from seven wells, two of which were produced from the Paleocene reservoir. The Gradient Boosting Regressor (GBR) produced promising results with the demarcation of thin sands with high accuracy levels. Based on a successful petro-elastic relationship, thin gas sands were highlighted. The low VCL of 30% and Sw of 45% cut-off reflect gas sands with P-impedances of 7500–9500 m/s × g/cc and a Vp/Vs ratio of 1.4–1.6 as decisive ML characteristics. Based on the applied workflow aided by ML, three reservoir units have been assigned for the Paleocene hydrocarbon-bearing sands, and gas sand probability distribution maps have been developed for each reservoir unit. Aligning the seismic inversion technique with machine learning advanced algorithms not only speeds up the prediction of elastic properties for facies classification but also increases accuracy to over 90% while drastically reducing uncertainty and associated costs in the process. Advanced machine learning algorithms have allowed us to cater to thin sand beds by eliminating the need for injecting frequencies. Instead, it recognizes features from the well data, trains itself, and predicts the corresponding features on the seismic trace, thus effectively allowing us to characterize the beds that are below seismic resolution in any given complex geology. The generated probability distribution maps of the three recognized thin-bedded sand units can be the basis for petroleum exploration and development in the study area. The discussed technique is successfully applied to complex folds and thrust belts, and hence can be implemented successfully in other heterogeneous thin-bed reservoirs for the successful classification of hydrocarbon-bearing sand distribution. It would optimize the results in a short period of time and with fewer economics.

Application of Time-Frequency Decomposition and Seismic Attributes for Stratigraphic Interpretation of Thin Reservoirs in Onshore Fuba Field Niger-Delta, Nigeria

Application of time-frequency decomposition and seismic attributes for stratigraphic interpretation of thin reservoirs in Onshore Fuba Field Niger Delta, Nigeria, are here presented, using Well-log and 3D Seismic data. Well-to-seismic tie, fault mapping, horizon mapping, time surface generation, depth conversion and seismic attributes generation were carried out using Petrel software. Structural interpretation of seismic data reveals a highly faulted field. Two distinct horizons were mapped. Fault and horizon interpretation shows closures that are collapsed crestal structures bounded by two major faults. All the interpreted faults are normal synthetic and antithetic faults which are common in the Niger Delta basin. The depth structure maps reveal anticlinal faults. Reservoirs are found at a shallower depth from 6500 to 7500 ft and at a deeper depth ranging from 11500 to 13000 ft. The variance and chaos values range from 0.0 to 1.0. The Variance edge and chaos analysis were used to delineate the prominent and subtle faults in the area while the produced spectra were used to delineate the stratigraphy and thickness of the thin-bedded reservoirs. The results of spectral decomposition at frequencies between 12Hz and 35Hz indicate some thin pay sand zones reservoirs which were characterized by of low frequency and high amplitude associated with known hydrocarbon zones, meandering channels, lobes and the presence of small scale faults in the field. Six new probable zones (Prospects A, B, C, D, E and F) of hydrocarbon accumulation were identified. The results of the study will help in the recovery of more hydrocarbon as by-passed zones and subtle structures are revealed in the area of study.

Seismic attributes and static reservoir simulation applications for imaging the thin-bedded stratigraphic systems of the Lower-Cretaceous Lower Goru fluvial resources, Pakistan

• Constructed workflow is a vital case for discovery of gas-bearing fluvial stratigraphic traps. • The SRSN resolves the thin-bedded point bar sandstone deposits in the basin. • AI and thicknesses for point bars sandstone are -0.214 to -0.219 g/c.c.*m/s and 17 to 19 m. • SRSN image sedimentary facies during the sea-level rise and fall events. Fluvial depositional systems accommodate a variety of primary stratigraphic-based trapping pools (STP) such as the channelized sands (CS) and point bars (PB). When they are encased within the non-porous and compacted shales, they develop hydrocarbon-bearing reserves. However, these STP are developed during the rapidly rising sea level and very slow fall, which creates hurdles in the development of accommodation space to accumulate the thin-bedded (hydrocarbon-bearing) and coarse-grained PB. PB are the primary stratigraphic traps within the fluvial hierarchy. Therefore, they require sophisticated tools such as reflection-based impedance reservoir simulations to simulate the thickness, accommodation space, proximal and distal locations, and sealing configurations of PB from a 3D perspective. The conventional seismic amplitudes are not sufficient enough to quantitatively portray these seismic sedimentological attributes due to a lack of preserved amplitudes and tuning frequency content aimed at fluvial-dominated clastic sequences. Therefore, the ultimate goal of conducting this research work is to detect thin-beds of PB and CF aimed at accumulating and generating hydrocarbon-posture STP. These thin-bedded reservoir facies are very delicate in tuning the frequency of the sub-surface systems. They require amplitude-based seismic data interpretation tools such as amplitude-based seismic attributes and inverted reservoir simulations. These tools can image the exact thickness of the reservoir lithology and types of fluids compared to the bandlimited geometrical attributes. Generally, the inverted reservoir simulations reconstruct the reflection-based impedances for the stratigraphic reservoirs, which helps in the quantification of the sub-surface thin-bedded stratigraphic systems. Therefore, the amplitude-based seismic attributes and thin-bedded wedge static reservoir simulation (SRSN) tools in Pakistan's Indus Basin. The amalgamated root-mean-square (RMS)-based seismic amplitude and frequency highlighted a full of twist continuous meander channel with a sinuosity index (S.I) > 2.7. Strong low-frequency shadows are observed at 23 Hz magnitudes that authorize the restoration of petroleum-posture fluvial-dominated PB STP. The amplitude attenuation model using the continuous wavelet transform (CWT) showed attenuation of spectral energy below the PB. The SRSN determined a 16 m thickness of STP using a constant velocity of 3449 m/s, which pinched out in the east of the Indus Basin. The predicted physical attributes from SRSN and their cross-plots against the thickness constraint have discriminated against the dominant sedimentary facies of the fluvial system during the significant rising and negligible falling sea levels. The predicted physical parameters have enabled vigorous controls aimed at developing accommodating intervals that have stored a significant amount of hydrocarbon-bearing PB. The quantitative characterization has enhanced acoustic impedance [AI] [g/c.c.*m/s] and thickness of PB with a strong correlation coefficient of R 2 >0.93. The predicted AI [g/c.c.*m/s] and thicknesses [m] aimed at PB were -0.214 to -0.219 g/c.c.*m/s and 16 to 19 m, respectively. Therefore, the SRSN can be used as a dynamic instrument for the accurate prediction of AI [g/c.c.*m/s] and thickness for the characterization of fluvial systems. This workflow may serve as a vital example for exploring the oil and gas-bearing stratigraphic system within the Indus Basin and similar basin settings.

Joint PP-PS seismic prestack inversion of thin-bed reservoirs

Abstract Thin beds are significant targets in seismic exploration of lithological reservoirs. The conventional Amplitude Versus Offset/Angle (AVO/AVA) inversion methods are based on Zoeppritz equations and their approximate formulas under single-interface assumptions, which are not suitable for thin-bed problems. Therefore, AVO/AVA inversion methods for thin-bed reservoirs are needed in high-resolution seismic exploration. Based on approximate reflection coefficients of a thin bed, this paper proposes a joint PP-PS prestack inversion method of thin-bed reservoirs using a least-squares approach. The method directly predicts elastic properties, including P-wave velocities, S-wave velocities and densities, as well as thin-bed thickness. In this study, four typical thin-bed models and an actual thin coal seam were used to prove applicability and superiority of the given inversion procedure. Compared to prestack inversion methods using exact Zoeppritz equations, our inversion method reveals thin-bed existence precisely, gives higher estimation accuracy and has better noise robustness. Future applications of the proposed inversion method are expected to advance seismic reflectivity techniques of thin-bed reservoirs, making it possible to detect potential source reservoirs with higher precision and accuracy.

Simulation Studies on Comparative Evaluation of Waterflooding and Gas Injection in Niger Delta Thin-Bed Reservoir

There is a need to increase ultimate recovery from petroleum reservoirs. In order to guarantee efficient resource extraction from reservoirs, primary recovery methods cannot be relied on throughout the life of a well. There is a time in the life of a reservoir when the primary energy will not be sufficient to ensure economic recovery. Complete abandonment of the reservoir at this point may not be a sound engineering decision given the huge investments in developing the asset. Secondary recovery methods present potentials for the recovery of the other trapped resources. The choice of the secondary recovery means depends on the reservoir and geologic conditions and should be determined by modeling and simulation. In this work, a simulation study is conducted for Niger Delta Field ABX2 to determine the performance of water-flooding and gas injection in the recovery of the asset after the primary recovery stage. ECLIPSE Blackoil simulator was used for the modeling and simulation. An equal reservoir rectangular grid block was designed for both the waterflooding and water injection comprising a total of 750 grid cells. Water and gas were injected in both cases at an injection rate of 11,000 stb/d and 300,000 scf/d for waterflooding and gas injection respectively. From the results of the simulation, it was realized that waterflooding gave a higher total oil recovery than gas injection. The difference in oil recovery from water-flooding and gas injection amounted to 0.08 MMstb/d. The Field Oil Recovery Efficiency (FOE) for waterflooding and gas injection was 38% and 16% respectively giving a difference of 22%. The waterflooding method was troubled with excessive water cuts due to water breakthroughs. Waterflooding was chosen against gas injection to be applied to Field ABX2 to improve recovery after primary production ceased.

Seismic prediction of oolitic beach thin-bed reservoir based on favorable facies belt constraints: Taking the second member of Feixianguan Formation in Jiulongshan area, Northwest Sichuan, China

The second member of Triassic Feixianguan Formation in Jiulongshan area of northwestern Sichuan Basin has made breakthroughs in natural gas exploration and has great exploration potential. Drilling data show that the second section of Feixianguan Formation has developed multiple sets of reservoirs, which are mainly concentrated in the upper sub-member of the second member of Feixianguan Formation. The overall heterogeneity is strong, the lithology and physical properties are complex and changeable, the reservoir thickness is thin, and drilling is less, so it is difficult to determine the spatial distribution characteristics of oolitic beach reservoir, which restricts the natural gas exploration process in this area. For the oolitic beach reservoir in the upper sub-member of the second member of Feixianguan Formation of Jiulongshan area, using downhole reservoir characteristics and 3D seismic data, the reflection characteristics of oolitic beach reservoir are analyzed, and then the seismic response model of oolitic beach reservoir is established by forward modeling. It is clear that the seismic response characteristics of the reservoir in this area are weak amplitude-continuous reflection; through the use of layer flattening impression method to restore the ancient landscape of the second section of Feixianguan Formation, combined with seismic facies analysis and seismic amplitude attribute characteristics, The distribution characteristics of favorable facies belt for oolitic beach development are determined. Based on the distribution of favorable facies belt, this paper uses the relative impedance-based tuning amplitude inversion and waveform difference inversion method to make a fine prediction of the spatial distribution of the reservoir, defines the spatial distribution characteristics of the reservoir, and predicts the thickness and fracture development of oolitic beach reservoir. The prediction results of the reservoir thickness are in good agreement with the actual drilling results, which confirms the application of this prediction method in this area. According to the fracture development, wave impedance value less than 1.6×106 g/(cm2·s), reservoir thickness, and other indicators, the favorable development area of oolitic beach reservoir is further delineated, which provides a favorable basis for the next exploration and development.

Frequency-dependent AVO analysis: A potential seismic attribute for thin-bed identification

Identifying thinly bedded reservoirs is important in exploration, appraisal, and development. The thin beds that we are referring to are of meter scale or less. Conventional seismic attributes are not able to resolve thin-bed effects. A new frequency-dependent amplitude variation with offset (FAVO) seismic attribute is developed for the prediction of thin beds. It is based on seismic wave scattering theory for vertically inhomogeneous media, in which the seismic response from a laterally homogeneous interval is represented by the Born series. The Born series characterizes the P-P and P-SV wave reflections, transmissions, and interbed multiples within the target interval with different order terms. The newly derived attribute corresponds to the second-order term of the Born series, in which P-S wave reflection and transmission energy is taken into consideration, and it is called the second-order FAVO gradient attribute. In a thinly bedded interval where sand/shale interfaces are abundant, the P-SV wave mode conversions are numerous. This leads to a strong second-order FAVO gradient attribute response compared to that of a blocky sand, silt, or shale interval under the assumption that there is no significant rock- and fluid-property differences between the intervals. Therefore, the new seismic attribute has the potential to be a thin-bed interval indicator. We have adopted a strategy to estimate the new attribute using conventional P-wave seismic data. The attribute is extracted from seismic data at the frequency range at which the second-order scattering effect is the most prominent. Synthetic and field data examples from offshore Trinidad are studied to demonstrate the second-order scattering effect and the potential usage of the second-order FAVO attribute for thin-bed reservoir characterization.

Multiscale evaluation of a thin-bed reservoir

A thin-bed laminated shaly-sand reservoir of the Miocene formation was evaluated using two methods: high resolution microresistivity data from the XRMI tool and conventional well logs. Based on high resolution data, the Earth model of the reservoir was defined in a way that allowed the analyzed interval to be subdivided into thin layers of sandstones, mudstones, and claystones. Theoretical logs of gamma ray, bulk density, horizontal and vertical resistivity were calculated based on the forward modeling method to describe the petrophysical properties of individual beds and calculate the clay volume, porosity, and water saturation. The relationships amongst the contents of minerals were established based on the XRD data from the neighboring wells; hence, the high-resolution lithological model was evaluated. Predicted curves and estimated volumes of minerals were used as an input in multimineral solver and based on the assumed petrophysical model the input data were recalculated, reconstructed and compared with the predicted curves. The volumes of minerals and input curves were adjusted during several runs to minimalize the error between predicted and recalculated variables. Another approach was based on electrofacies modeling using unsupervised self-organizing maps. As an input, conventional well logs were used. Then, the evaluated facies model was used during forward modeling of the effective porosity, horizontal resistivity and water saturation. The obtained results were compared and, finally, the effective thickness of the reservoir was established based on the results from the two methods.

Spectral decomposition' application for stratigraphic-based quantitative controls on Lower-Cretaceous deltaic systems, Pakistan: Significances for hydrocarbon exploration

Shoreface deltaic depositional systems (UDS) form excellent stratigraphic traps. The UDS are developed during the adverse sea-level conditions, which have a vital impact on the quantitative prediction of stratigraphic reservoirs. The prediction of accurate thickness and distribution of porous reservoir along the UDS is always a challenging job for exploration geophysicist. Since these oil and gas plays are purely thin-bedded reservoirs. They require a specific tuning frequency to resolve and predict the accurate thickness of the hydrocarbon-bearing zone. The band-limited seismic attributes are not reliable tools for developing cost-effective stratigraphic plays. The Fourier transformation tool such as continuous wavelet transforms (CWT) and thickness modelling for UDS (TMUDS) are executed on the gas-bearing UDS, Pakistan. Beyond the conventional amplitudes, the 37-Hz tuning block demarcates the gas-bearing reservoirs. The amplitude attenuation at 48-Hz validates the presence of coarse-grained sediments within the upper shoreface intervals of deltaic system. The blending of seismic, 37-Hz, and sweetness magnitudes completely recognizes the dominant reservoir fluids, which were unable to detect using the traditional mapping. The sweetness profile predicts a 20 m thick reservoir facie. The band-limited TMUDS reveals some tuning effects of ambiguous lithology and fluids. However, the post-stack seismic data processing within the designed amplitude spectrum of 12–55 Hz have greatly enhanced the physical parameters of thickness and presence of hydrocarbons. The 36-Hz trace sub-bands have predicted a 48 m thick reservoir facie along the UDS. The 36-Hz ESB confirms the presence of hydrocarbon-bearing coarse-grained deltaic facies, which are accumulated along the intersection point of shelf-slope of UDS. The quantitative plots of predicted thickness and acoustic impedances [AI] [g/c.c.*m/s] at 36-Hz CWT shows a strong correlation coefficient of R2 > 0.90. These observations take a lead over the band-limited amplitude-based seismic attributes for quantification for UDS. Hence, only the post-stack seismic data processing and interpretation based on the CWT wavelet can enhance the vertical thickness of the reservoir and the lateral extent with the least error. This workflow has robust stratigraphic implications for explorations for stratigraphic fairway for Lower Goru and acts as an analogue for local to regional clastic depositional systems within Asia and world similar depositional settings.

Mapping of thin sandstone reservoirs in bisol field, Niger delta, Nigeria using spectral decomposition technique

This study focuses on using spectral decomposition (SD) technique to characterize complicated reservoirs to understand the structural and stratigraphic variations in the interpreted horizons from Bisol field. The purpose of this study is to use geophysical and well logging data sets to map the thin-bedded sandstone reservoirs and prospect zones within the multiple reservoirs in Bisol field, Niger Delta. The interpretation of faults and horizons was carried out on the seismic section, which was further used to produce the structural maps. Seismic attributes such as trace and variance were used to enhance the truncated structures from the seismic section, while the produced spectra were used to delineate the stratigraphy and thickness of the thin-bedded reservoirs. Thin sandstone reservoirs were identified from well logs and consequently mapped on the seismic section. Fast Fourier Transform workflow was successfully used to image the stratigraphic features in the study area. Three horizons (S1T, S2T and S3T) were delineated from the seismic section, and four reservoirs were mapped and correlated across the wells. Frequency analyses from the seismic sectional view revealed some thin pay sandstone reservoirs, which were characterized by high amplitude. Three new probable zones (Prospect A, B and C) of hydrocarbon accumulation were identified using the SD technique.

INTEGRATED LAMINATED SHALY SAND ANALYSIS (LSSA) AND MONTE CARLO UNCERTAINTY PROBABILISTIC APPLIED FOR THE THIN LAMINATION RESERVOIR TOWARDS SIGNIFICANT NET PAY ADDITION

In recent years, formation evaluation and well logging analysis have been evolving from its measurements, accuracy and applicability to determine tough downhole environments. Thin bed Reservoir is one of the most challenging well logging analysis due to the complexity of the high content of clay minerals in the shaly-sand lamination layer (thin bed) which inherently affects the log data response in the form of high gamma ray values and low resistivity. This causes the thin lamination zone is identified as a non-reservoir zone. Meanwhile, worldwide 30 to 40% of the oil in-place resources are confined within thin beds. Seeing the problem in the prediction of thin bed reservoirs, this research is focusing on Enhancing and developing thin bed potential by reevaluating petrophysical analysis, applying Laminated Shally Sand Analysis and Monte Carlo Uncertainty Probabilistic for calculating petrophysical parameter distribution and validating the parameter with Log Image. Laminated Shally Sand Analysis implements Thomas Steiber Plot in order to give laminated shale distribution and porosity, whereas the water saturation is calculated using Waxman Smith’s Equation. From this research, well SSK has thin bed potential at 2521.45 - 2543.45 ft. Laminated Shally Sand Analysis also capable to improve thickness of netpay with the range of 40.35% based on probabilistic delivered from Monte Carlo.

Seismic sedimentology of lacustrine delta-fed turbidite systems: Implications for paleoenvironment reconstruction and reservoir prediction

Abstract The deltaic-turbidite systems are common features in continental lacustrine rift basins. In the Bohai Bay rift Basin, Eastern China, the turbidite sandstones are the critical targets for hydrocarbon production and development. However, their intricate sedimentary patterns and the small size of the reservoirs introduces more challenge for their understanding and prediction. Through seismic sedimentology workflow, 90°-phase adjustment, strata slicing, spectral decomposition, RGB color blending technique, and geobody extraction, 3D seismic data and wireline log information data are integrated to understand the historical evolution of delta-turbidite systems and predicting the spatial and temporal distribution of sandbodies of the Es3m sub-member in the Shahejie Formation, dongying depression. The study identifies two system tracts in the study area, transgressive and highstand system tracts, from seismic and wireline logs interpretation. We identified six fourth-order sequences within the highstand system tracts, each of which corresponds to a different period of deltas progradation. Stratal slicing mapping on multiple deposition surfaces reveals the high-resolution historical evolution of the delta-turbidite systems and the distribution of their associated sandbodies. Interpretation of slices shows six stages of deltas development, which led to widespread delta-fed turbidite reservoirs. Three multi-delta-turbidite systems: the northern fan-turbidite systems and the southeast-turbidite systems are documented, which evolved throughout all stages of delta development. Rapid progradation of multi-deltas systems played an essential role in the evolution and development of thin-bedded reservoirs in the HST. Faults and local topographic lows controlled the spatial distribution of sandbodies in the area. The individual sandbodies range from 4.48 km2 to 16.49 km2 in size, and they vertically superimposed from bottom to top. The classification scheme presented in this work shows a successful application in terms of paleoenvironmental reconstruction and reservoir prediction of the delta-fed turbidite systems, which can be applied to similar systems worldwide.

Designing a pragmatic solution for complex numerical modeling problem in thinly laminated reservoirs

Unquestionably, water breakthrough into the producing wells is one of the biggest threats to the development and production of oil and gas reservoirs around the world. The predicted water production profile from a numerical simulation model directly affects the estimated recoverable volumes and hence the decision making process for the field development and the facility design to handle the produced water. The problem of reliably predicting the water production profile exacerbates when dealing with thinly laminated sand reservoirs. Calculating the total water saturation (SWT) using well log data in the hydrocarbon zone in this type of reservoirs is adversely affected by the convoluted readings of the conventional logging instruments whenever the resolution of the laminations goes beyond the tool resolution (i.e. 0.5 feet). This in turn leads to unrealistic movement of water in the model, pre-mature water breakthrough, pessimistic forecast of oil and gas and over-estimation of required water treatment system capacity. Although some advancement has been made in the identification of these types of reservoirs, their reservoir modeling still remains a challenge for petroleum industry due to limitations in developing proper methods to estimate petrophysical properties using conventional logs and also the computational cost of running extremely fine numerical models. In this study various issues and challenges of modeling these types of reservoirs are addressed. A workflow for numerical modeling of thinly laminated sands at affordable vertical grid resolutions has been proposed that properly uses the available geological, petrophysical and engineering data in an effective (vs. total porosity) system. The methodology of reproducing the volumetrics and capturing heterogeneity at various scales, through proper rock-typing and use of net to gross ratios are discussed in detail. The data requirement for modeling, reservoir management and performance monitoring of thin beds is also elucidated. The presented workflow provides a simple yet pragmatic tool that can help best represent the thinly laminated sands at affordable measurement and computation costs, mitigate the risks associated with thin bed reservoir development and increase the value of field development planning.

Characterization of thin bed reservoirs of Linch area, Cambay Basin using complex trace transform method to enhance temporal resolution of seismic data

In the last few decades, the interest in thin hydrocarbon reservoirs has grown progressively justifying the great effort spent on developing techniques for quantitative interpretation of thin bed seismic response. The detection and resolution of reflections from thin layers are major problems in reflection seismic. Many a times it is difficult to precisely estimate the vertical and lateral extensions of a significant portion of discovered hydrocarbon reservoirs due to the thin layer effect. In Linch area of Cambay basin, the sands which are dispersed especially within Older Cambay Shale (OCS) are thin and discrete in nature and are not properly discernible on seismic, in particular at deeper levels; some of these sands hold commercial oil and gas. Even within shallower Kalol formation most of the sands are quite thin to be delineated by conventional seismic interpretation. A small part of Linch area comprising of six wells, namely, LN-A, LN-B, LN-C, LN-D, LN-E, LN-F has been taken up for this study (Figure 1). Log characteristics and corresponding seismic response for well LN-A shows that the sands which are dispersed especially within Older Cambay Shale (OCS) are thin and discrete in nature and are not properly discernible on seismic surveys, in particularly at deeper levels. Sands being thin, the seismic response is of composite nature arising out of several sand-shale alterations (Figure 2). Rock physics analysis based on well logs indicates the porous sands to be having impedance within the range of shale impedance, mostly towards higher order (Figure 3). Inversion using conventional approach turns out to be of no practical use. In this study authors have investigated the approach for thin reservoir evaluation through complex trace transform (CTT) method.

Hybrid clustering-estimation for characterization of thin bed heterogeneous reservoirs

Modeling heterogeneous reservoirs is cumbersome as it requires a great effort to determine the variation of properties with respect to direction, while the lack of adequate data makes this a difficult task. Generating static models for heterogeneous reservoirs remains an important challenge in petroleum engineering applications which requires more investigations. Some heterogeneous reservoirs, such as thin bed reservoirs, may be divided into some homogeneous subzones where characterization of these homogeneous sub-reservoirs and their integration can represent the properties of the heterogeneous reservoir. To investigate this concept, in this paper, three exemplar reservoirs (ER) were generated. The heterogeneity in the data is increased from ER1 to ER2 and ER3. In the first step, each reservoir was studied as one single zone, so the results can be compared with the proposed method in this work. Ordinary kriging (OK) and multilayer perceptron neural network (MLP) were used for modeling of these exemplar reservoirs. This study showed that OK cannot model reservoir characteristics, whereas the MLP yielded reasonably acceptable results. In the next step, a hybrid clustering classification-based method was applied to divide the reservoir to homogeneous subzones. Each reservoir was modeled in terms of its homogeneous subzones. The homogeneous subzones were modeled using OK and MLP. The results showed that the developed model was successful in modeling the heterogeneity at a reasonable CPU processing time. Also, it was seen that in case of using the simple modeling techniques, MLP neural network yields more reasonable results, compared with OK.

Study and Application of Hydraulic Jet Radial Drilling in Carbonate Reservoirs

The hydraulic jet radial drilling technology is a low-cost production and completion technology for effectively developing low-permeability marginal reservoirs, thin-bed reservoirs with edge and bottom water, and depleted oil and gas fields. It has been successfully and widely applied in sandstone, coalbed methane, and heavy oil reservoirs. In order to explore its application in carbonate reservoirs, specially economically and efficiently develop low-permeability thin-layer carbonate reservoirs, the pilot of hydraulic jet radial drilling technology in the carbonate reservoir application was successfully completed through the research on the principle, advantage, existing problems and application condition of radial jet drilling, economic productivity was got, and cost-effective development was achieved, this pilot provided a method for the development of low permeability thin layer carbonate reservoir. This research shows that the hydraulic jet radial drilling technology has its unique technical advantages, which can enable some reservoirs to increase production or injection, but it is not suitable for every well, it has certain applicable conditions, such as the depth, thickness, and temperature of the target zone, and the conditions of well inclination, casing and wellbore have certain requirements too. The hydraulic jet radial drilling technology can achieve the expected target based on the zone and well selection, in selecting layers, as far as possible, homogeneous oil layers with good reservoir physical properties should be selected; the key of its successful implementation is the depth and azimuth control, wellbore diameter and operation safety control. The application of hydraulic jet radial drilling in carbonate reservoirs will make the spray hose wear large due to its high Young's modulus the high hardness, which affects the treatment footage; the use of acid in jet drilling can increase the radial drilling footage, but on the other hand can also produce impurities affecting the operation. The working fluid for jetting must meet the requirements of no solid phase.

Accuracy of wavelets, seismic inversion, and thin-bed resolution

Broadband reprocessed seismic data from the North West Shelf of Australia were inverted using wavelets estimated with a conventional approach. The inversion method applied was a facies-based inversion, in which the low-frequency model is a product of the inversion process itself, constrained by facies-dependent input trends, the resultant facies distribution, and the match to the seismic. The results identified the presence of a gas reservoir that had recently been confirmed through drilling. The reservoir is thin, with up to 15 ms of maximum thickness. The bandwidth of the seismic data is approximately 5–70 Hz, and the well data used to extract the wavelet used in the inversion are only 400 ms long. As such, there was little control on the lowest frequencies of the wavelet. Different wavelets were subsequently estimated using a variety of new techniques that attempt to address the limitations of short well-log segments and low-frequency seismic. The revised inversion showed greater gas-sand continuity and an extension of the reservoir at one flank. Noise-free synthetic examples indicate that thin-bed delineation can depend on the accuracy of the low-frequency content of the wavelets used for inversion. Underestimation of the low-frequency contents can result in missing thin beds, whereas underestimation of high frequencies can introduce false thin beds. Therefore, it is very important to correctly capture the full frequency content of the seismic data in terms of the amplitude and phase spectra of the estimated wavelets, which subsequently leads to a more accurate thin-bed reservoir characterization through inversion.