Reservoir Lithofacies Research Articles

An integrated approach to lithofacies characterization of a sandstone reservoir using the Single Normal Simulation equation: A Case study

This paper describes a comprehensive approach to improved lithofacies characterization using the simultaneous pre-stack inversion, Bayesian classification, and multiple-point geostatistics. This integrated workflow provides an enhanced lithofacies characterization by reproducing the continuity of geological facies in the meandering-fluvial sandstone reservoir from Upper Assam, India. The simultaneous pre-stack inversion provides the rock elastic properties of the reservoir, such as P- impedance, s-impedance, density, and VP/VS ratio. Next, the probabilistic modeling approach of Baye's theorem is used to integrates seismic elastic properties with well log lithofacies identified from the cross-plot analysis for probability volumes of lithofacies. Finally, the multiple-point geostatistics based on the Single Normal equation Simulation algorithm is used to generate the improved lithofacies model by constraining of the lithofacies probability volumes (soft data) and well logging data (hard data). These results were compared with the Bayesian lithofacies classification and proved that the adopted method had successfully improved the continuation of the reservoir lithofacies by reproducing the lithofacies, hence an improvement in the reservoir characterization.

Hierarchical reservoir lithofacies and acoustic impedance simulation: Application to an oil field in SW of Iran

In this study, a hierarchical simulation algorithm was implemented to produce 3D models of lithofacies and acoustic impedance (AI) in an oil field in southwestern Iran. Hierarchical simulation is a powerful method that takes into account the spatial distribution and hard contact relationships of continuous variables within the categorical variables in reservoir characterization. To implement the hierarchical simulation algorithm in this study, pluri-Gaussian simulation was used to construct the layouts of one categorical variable (lithofacies domains) and turning bands simulation was used to produce one continuous variable (AI models) within each simulated domain. The dataset that is available to test the proposed method includes the lithofacies and AI logs of seven wells. For validation of the proposed model, one of wells was excluded from the initial dataset to check the accuracy of results. The algorithm was implemented on a gridded model to produce 50 realizations of 3D lithofacies and AI models. The statistical analyses of the produced models verified the capabilities of hierarchical simulation in reproducing the lithofacies domains and AI values related to each domain. The simulated AI models were compared with the seismic inversion model to corroborate the reliability of the results. In addition, to show the superiority of the hierarchical approach, the results were compared to the results of direct AI modeling in which the AI models were generated without considering any lithofacies data. The comparisons in the blind well indicated a high correlation between the modeled values and the true AI. The correlation coefficient between average AI models of the hierarchical approach and the true AI was 0.85. Whereas, this value was 0.75 for the average of directly simulated AI models and 0.74 for the seismic inversion, respectively. Histogram analysis also verified the capability of the hierarchical modeling in reproducing the statistical properties of the original data. The resulting AI model obtained using the method proposed in this study also showed a high compatibility with the deterministic seismic inversion cube.

Facies analysis and petrophysical investigation of the Late Miocene Abu Madi sandstones gas reservoirs from offshore Baltim East field (Nile Delta, Egypt)

The Nile Delta has become an economically important region of Egypt, because of large-scale natural gas and oil discoveries in recent decades. The offshore Baltim East field is one of the Nile Delta's major gas producers from the upper Miocene clastic reservoirs, but detailed lithofacies and petrophysical analyses of the Abu Madi gas reservoir have not been conducted to date. This study investigates the petrographical and petrophysical properties of the upper Miocene Abu Madi Formation from the Nile Delta to infer the lithofacies distribution, depositional environments, and reservoir qualities of the Level 3 Main and Lower sands. In this work, we used a variety of data sets, including core samples, petrophysical measurements, and well logs, to identify the most important characteristics of these sandstone reservoirs. Both reservoirs are hydrostatically pressured and exhibit a gas gradient of ∼2.26 MPa/km. We have identified six different lithofacies from the two reservoirs. SEM and thin section analyses indicate that trough cross-bedded (F-1), parallel laminated (F-2), and massive sandstones (F-6) are the primary reservoir lithofacies composed of texturally immature subfeldspathic quartz arenites. These sandstones have sharp bases and exhibit fining-upward trends with ripple laminated siltstone (F-3), heterolithic silt and clay (F-4), and laminated claystone (F-5) facies lying on top. We inferred the reservoir depositional environment as fluvial channels and sequence stratigraphically these incised valley-fills represent low stand systems tract. The reservoir sandstone facies show good porosity (10–28%), mostly interparticle. Chlorite coatings around quartz grains are abundant, while pore-filling kaolinite is the dominant porosity-destroying clay phase. Grain dissolution introduced secondary intergranular porosity along the potassium feldspar cleavage planes within the F-1 lithofacies. Porosity, permeability, and reservoir quality parameters (RQI, NPI, and FZI) calculated from routine core analysis indicate that the F-1 and F-6 lithofacies have excellent hydraulic flow properties with >100 mD permeability, RQI>1 μm and FZI >5 μm, while the fine-to very fine-grained F-2 offers poor to fair reservoir quality defined by a wide permeability range of 0.1–2150 mD. The clay and silt-dominated lithofacies (F-3, F-4, and F-5), due to their impervious nature, act as intra-reservoir vertical permeability barriers. The differences in rock composition and facies control diagenesis and physical properties of the reservoir. The results presented, provide further insight into the exploration of the fluvial channel deposits and regional reservoir quality of the upper Miocene Abu Madi Formation of the Nile Delta.

3D geo-cellular static virtual outcrop model and its implications for reservoir petro-physical characteristics and heterogeneities

Geostatistical data plays a vibrant role for surface-based reservoir modeling through outcrop analogues, which is used to understand three-dimensional (3D) variability of petrophysical properties. The main purpose of this study is to improvise the surface-based 3D geo-modeling to demonstrate petrophysical characteristics and heterogeneities of Sandakan reservoirs, NW Borneo. We used point cloud data from Light Detection and Ranging (LiDAR) to build high-resolution virtual outcrop modeling (VOM) onto which we mapped 6 different lithofacies. Porosity and permeability of core plugs were measured to determine the average variance of petrophysical properties for each lithofacies. By utilizing the integration of VOMs analogues and petrophysical properties in Petrel™, we demonstrated the distribution and associations of all lithofacies in pseudo wells that have inherent thin beds heterogeneities in 3D geo-cellular model. The results concluded that the heterogeneity of thin beds in lithofacies is dependent on porosity and permeability with input dataset. According to the final model, cross-bedding sandstone (CBS), hummocky cross-stratified sandstone (HCSS) and trough cross-bedding sandstone (TCBS) show good reservoir quality due to high porosity ranging from: 25.6% to 20.4% and, 19.3%–14.5%, and permeability ranging from: 74.03 mD to 66.84 mD and, 64.86 mD to 21.01 mD. In contrast, massive to weak laminae sandstone (MWLS) and bioturbated sandstone (BS) show fair to poor reservoir quality, caused baffling of surrounding mud sediments in the reservoir lithofacies. Results also revealed that LiDAR based VOM with petrophysical properties can significantly reduce the risk and minimize the cost of reservoir modeling in petroleum industry.

Pore Structure and Movable Fluid Characteristics of Typical Sedimentary Lithofacies in a Tight Conglomerate Reservoir, Mahu Depression, Northwest China

The pore structure and movable fluid characteristics of tight conglomerate reservoirs are complex, which are greatly different from conventional reservoirs. The depositional mechanism is the fundamental factor controlling the physical properties of conglomerate reservoirs. However, there is a lack of systematic research on the pore structure and movable fluid characteristics of conglomerate reservoirs with typical sedimentary facies. This paper investigates the pore structure and movable fluid characteristics of conglomerate of different sedimentary facies based on various experiments. Casting thin sections, X-ray diffraction, scanning electron microscopy, high-pressure mercury injection, and nuclear magnetic resonance experiments were conducted on 32 conglomerates samples from the Mahu Sag, Junggar Basin, China. The quality classification method of tight conglomerate reservoirs is established. The results show that the conglomerate can be divided into three sedimentary facies; traction flow conglomerate (TFC) and pebbled sandstone (PSS) mainly develop intergranular pores and dissolved pores; and the pore diameter curves are mainly a double peak, single peak, and flat peak. Gravity flow conglomerate (GFC) mainly develops dissolved pores and interstitial micropores, and the pore diameter curve is mainly a single peak. PSS includes pebbled gritty sandstone (P(G)SS) and pebbled fine sandstone (P(F)SS). TFC and P(G)SS are favorable class I reservoirs, while GFC and P(F)SS are nonfavorable class II reservoirs. A new parameter, the ratio of the major axis to the minor axis of the pore outer ellipse (axial ratio), is proposed to quantitatively describe the compaction effect. The average axial ratios of the three lithofacies are 3.04, 3.98, and 8.78, respectively, indicating that the compaction is intensified and the pore structure becomes worse. By analyzing the correlation between pore structure parameters and permeability, it is found that the main controlling factors of permeability of GFC and TFC are sorting and connectivity, respectively, and the main flow radius is the most suitable parameter to describe permeability. A linear spectral decomposition method was used to establish a new quantitative calculation method of movable fluid saturation for different types of pores, and the results show that the movable fluid saturation of intergranular pores is the highest (average: 65.43%), and the movable fluid saturation of TFC and P(G)SS with more intergranular pores is the highest. Movable fluid saturation is inversely proportional to the content of I/S and the compaction rate and positively proportional to the content of quartz and feldspar and the cementation rate. The fluid mobility of water-wet samples is weaker. The research results provide theoretical support for the identification of favorable reservoirs and the cognition of a development mechanism.

Seismic Lithofacies Distribution Modeling Using the Single Normal Equation Simulation (SNESIM) Algorithm of Multiple-Point Geostatistics in Upper Assam Basin, India

Recently, multiple-point geostatistical simulation gained much attention for its role in spatial reservoir characterization/modeling in geosciences. Accurate lithofacies modeling is a critical step in the characterization of complex geological reservoirs. In this study, multiple-point facies geostatistics based on the SNESIM algorithm integrated with the seismic modeling technique is used as an efficient reservoir modeling approach for lithofacies modeling of the fluvial Tipam formation in the Upper Assam Basin, India. The Tipam formation acts as a potential reservoir rock in the Upper Assam Basin, India. Due to the basin geological complexity and limitation in seismic resolution, many discontinuities in depositional channels in this fluvial depositional environment have been identified using conventional lithofacies mapping. This study combines three techniques to reproduce continuity of the lithofacies for better reservoir modeling. The first is simultaneous prestack inversion for inverting prestack gathers with angle-dependent wavelets into seismic attributes. A cross-plot of P-impedance and VP/VS ratio from well-log data was used to classify the different reservoir lithofacies such as hydrocarbon sand, brine sand, and shale. The second is the Bayesian approach that incorporates probability density functions (PDFs) of non -parametric statistical classification with seismic attributes for converting the seismic attributes into lithofacies volume and the probability volumes of each type lithofacies. The third technique is multiple-point geostatistical simulation (MPS) using the Single Normal equation Simulation (SNESIM) algorithm applied to training images and probability volumes as constraints for a better lithofacies model. These integrated study results proved that MPS could improve reservoir lithofacies characterization.

Reservoir lithofacies modeling using well logs and seismic data based on Sequential Indicator Simulations and Probability Perturbation Method in a Bayesian framework

In this paper, an inverse framework based on Bayes’ theorem is suggested for integrating well logs and seismic data into reservoir lithofacies modeling process. The proposed method is based on combination of the Sequential Indicator Simulation (SIS), and a stochastic optimization method (i.e. Probability Perturbation Method (PPM)). SIS is used to calculate the conditional probability of presence/absence of lithofacies indicators in each grid-block, and PPM is applied to update (perturb) the conditional probability used in SIS. A notable innovation presented in this study is using the Genetic algorithm’ crossover operator to increase the PPM exploitation capability. To demonstrate the efficiency of our proposed approach, the results of its application on a 3D test model is compared with outcomes of two commonly-used constraining approaches on SIS. Qualitative and quantitative analysis of the obtained results on 3D test model reveals a (23.8)% and (16.98)% (on average) improvement in consistency of lithofacies models generated using the proposed approach with the reference lithofacies model over the employed Vertical Probability Trend and Seismic Probability Trend constraining approaches on SIS, respectively. Besides, the obtained results show that implementing crossover operator leads to a 4.56% improvement in matching of the constructed lithofacies models with the reference model.

Pore aperture size (r36) calculation from porosity or permeability to distinguish dry and producing wells

Four hundred eighty sandstone core samples obtained from three different hydrocarbon charged formations of different geologic ages (Pliocene; Miocene and Cretaceous) and different geographic locations (Egypt and Hungary) are used to correlate the effective pore aperture size adopted by Winland (r35) and new r36 of the present work. These pore aperture percentiles (r35 and r36) are calculated with different empirical equations and correlated with each other to declare which one is effective, simple, and has no additional sources of error. In the present work, new r36 was calculated two times: first from porosity only (Or36) and the second time from permeability only (Kr36). Both are correlated to r35.The calculated coefficient of correlations between Or36 and r35 were (R2 = 0.54, 0.71, and 0.73) for the Bahariya, Szolnok, and El Wastani formations, respectively. However, the correlation between Kr36 and r35 is showing very high coefficient of correlations (R2 = 0.9963, 0.9927, and 0.9957) for the Bahariya, Szolnok, and El Wastani formations, respectively. The novel Kr36 could be very helpful to discriminate between dry (pore aperture size 0.5 μm or 5000 A°) in case of absent of porosity data. Model verification indicates a very close matching between Kr36 and Wr35 vertical profiles in Baltim level III main reservoir (Miocene in age). This confirms the beneficial application of Kr36, which is derived from permeability only, instead of Winland-r35 in all reservoir lithofacies.

Characteristics of lacustrine deepwater fine-grained lithofacies and source-reservoir combination of tight oil in the triassic chang 7 member in Ordos Basin, China

The lithofacies characteristics of fine sedimentary rocks affect the hydrocarbon generation capacity and reservoir performance of tight oil and are closely related to the sedimentary environment. On the basis of field outcrops and core observations, combined with logging data, thin section identification, grain size analysis, organic carbon analysis and physical property tests, the fine sedimentary facies of the Chang 7 Member in the Ordos Basin are studied. Nine lithofacies types are identified in the study area, including planar and trough cross-bedding sandstone facies (Spt), massive bedding sandstone facies (Sm), slump deformation fine sandstone facies (Ssd), sand-mud interbedded facies (Sb), rippled siltstones facies (Fr), horizontal bedding mudstone facies (Mh), massive bedding mudstone facies (Mm), horizontal bedding shale facies (S) and tuff facies (T). Lithofacies types Spt, Ssd, Fr are developed in the gentle slope belt in the northeastern study area, which is a delta front-semi-deep lake sedimentary environment and mainly contains underwater distributary channel and estuary dam sedimentary microfacies types. Lithofacies types such as Sm, Sb, Mh and T are developed in the southwestern steep slope zone of the study area, which is a channel-type gravity flow sedimentary environment, and sedimentary microfacies types such as near-source channels, far-source channels and leading-edge dolomites are developed. In the vertical direction, during the Chang 73 sedimentation period, the lake surface area and water depth reached their maxima, and S and Mh lithofacies developed, which were conducive to the formation of high-quality hydrocarbon source rocks for tight oil. During the Chang 72-Chang 71 sedimentation period, the lake basin shrank, and the reducibility of the water body weakened. The delta front sand body composed of Spt lithofacies in the northeast and the sandy clastic flow sand body composed of Sm in the southwest constitute the main tight oil reservoirs. High-quality hydrocarbon-generating lithofacies and favourable reservoir lithofacies are spatially superposed and developed, forming two source-reservoir combinations in the Chang 7 tight oil source-reservoir formation and near source-reservoir formation.

An integrated approach to distribute carbonate reservoir properties, using lithofacies and seismic attributes: a case study from SW of Iran

Complexity and heterogeneity of carbonate deposits make the understanding of the reservoir quality challenging. This study is a contribution to the understanding of the distribution of carbonate–evaporite reservoir property of the Permo–Triassic Kangan–Dalan succession in one of the giant gas fields in the southwest of Iran. To capture and describe the complexity and heterogeneity of the carbonate reservoir, we defined different rock properties approach to the management of quantitative data on carbonate reservoir which is based on well and seismic data with an integrated sedimentological investigation, petrophysical evaluation, and seismic analysis to determine the new reservoir lithofacies classification. A lithofacies-based reservoir characterization study was conducted carbonate reservoir to build a numerical 3-dimensional (3D) geological model including reservoir property prediction for reservoir flow simulation. To do this, full suite of logs from six wells, core from four wells in the studied interval and 3D seismic volume across the studied interval have been involved and investigated. Five lithofacies were identified from detailed analysis, and the relationship between lithofacies and reservoir property was considered and geostatistically propagated in the studied area. This study shows that an integrated study using seismic data and well logs can be used to basically divide the reservoir into relatively homogeneous zones based on core and petrophysical analysis, and then evaluate each zone to distinguish high-quality zones. This approach provides useful insight to Permo–Triassic carbonate reservoir and other similar reservoirs and can also be effectively used in areas which lack well or outcrop data.

Modeling Three-Dimensional Anisotropic Structures of Reservoir Lithofacies Using Two-Dimensional Digital Outcrops

Reservoir heterogeneity is a key geological problem that restricts oil and gas exploration and development of clastic rocks from the early to late stages. Existing reservoir heterogeneity modeling methods such as multiple-point geostatistics (MPS) can accurately model the two-dimensional anisotropic structures of reservoir lithofacies. However, three-dimensional training images are required to construct three-dimensional reservoir lithofacies anisotropic structures models, and the method to use reservoir heterogeneity model of fewer-dimensional to obtain a three-dimensional model has become a much-focused research topic. In this study, the outcrops of the second member of Qingshuihe Formation (K1q2) in the northwestern margin of the Junggar Basin, which are lower cretaceous rocks, were the research target. The three-dimensional reservoir heterogeneity model of the K1q2 outcrop was established based on the unmanned aerial vehicle (UAV) digital outcrops model and MPS techniques, and the “sequential two-dimensional conditioning data” (s2Dcd) method was modified based on a sensitivity parameter analysis. Results of the parametric sensitivity analysis revealed that the isotropic multigrid simulations demonstrate poor performance because of the lack of three-dimensional training images, conditioning data that are horizontally discrete and vertically continuous, and distribution of lithofacies that are characterized by large horizontal continuities and small thicknesses. The reservoir lithofacies anisotropic structure reconstructions performed well with anisotropic multigrids. The simulation sequence of two-dimensional surfaces for generating the three-dimensional anisotropic structure of reservoir lithofacies models should be reasonably planned according to the actual geological data and limited hard data. In additional to this, the conditional probability density function of each two-dimensional training image should be fully utilized. The simulation results using only one two-dimensional section will have several types of noises, which is not consistent with the actual geological background. The anisotropic multigrid simulations and two-dimensional training image simulation sequence, proposed in this paper as “cross mesh, refinement step by step”, effectively reduced the noise generated, made full use of the information from the two-dimensional training image, and reconstructed the three-dimensional reservoir lithofacies anisotropic structures models, thus conforming to the actual geological conditions.

Pore-scale oil distribution in shales of the Qingshankou formation in the Changling Sag, Songliao Basin, NE China

A total of 19 representative lacustrine shale (core) samples from the Upper Cretaceous Qingshankou Formation in the Changling Sag, Songliao Basin, northeast China have been characterized to determine the types of shale oil reservoir lithofacies and investigate pore structures and pore-scale oil distribution using an integrated petrographic, geochemical and petrophysical approach. Based on the sedimentary structures and mineral compositions, four lithofacies types have been recognized: foliaceous argillaceous mudstone (FAM), laminated diamictic mudstone (LDM), laminated felsic mudstone (LFM) and interbedded felsic mudstone (IFM). Sequential extraction experiments via a Soxhlet extractor were performed using different solvents to recover oils of varying polarities: weak-polar oil (WPO) was extracted with n-hexane under room temperature, while strong-polar oil (SPO) was extracted with a mix of dichloromethane and methanol (9:1 v/v) extraction. Low-pressure N2 sorption data acquired from the original and solvent extracted samples indicates that the pore volumes occupied by WPO (VWPO) decrease progressively in LFM (averaging 68.32 × 10−4 cm3/g), LDM (averaging 50.41 × 10−4 cm3/g), FAM (averaging 48.86 × 10−4 cm3/g) and IFM (averaging 39.39 × 10−4 cm3/g); while pore volumes occupied by SPO (VSPO) increase progressively in IFM (averaging 8.00 × 10−4 cm3/g), LFM (averaging 12.62 × 10−4 cm3/g), LDM (averaging 38.85 × 10−4 cm3/g) and FAM (averaging 65.08 × 10−4 cm3/g). Major factors controlling pore-scale oil distribution in the shale reservoirs include pore structures, TOC and clay mineral contents. Pore structures can affect the distribution of WPO and SPO to a great extent. WPO is mainly distributed in the mesopores, while SPO is present in all pores in the four lithofacies. SPO is mainly distributed in mesopores in FAM and LDM, and in macropores in LFM and IFM. TOC and clay mineral contents have strong impacts on the distribution of SPO. Carbonate minerals in LDM and IFM are dominated by ostracoda shells and authigenic calcite cement, respectively. The carbonate mineral content shows a positive correlation with WPO in LDM, in which the carbonate minerals are dominated by ostracoda shells with well-developed pores due to organic acid dissolution. TOC shows a positive correlation with WPO for TOC less than 1.2 wt%, while shows a negative correlation for TOC greater than 1.2 wt%. In the study area, LDM and LFM are identified as favorable lithofacies or “sweet spots” for shale oil exploration because they have relatively high TOC (0.7–2 wt%), high percentages of in situ WPO and a high mineral brittleness index.

Evaluation Methods of Profitable Tight Oil Reservoir of Lacustrine Coquina: A Case Study of Da'anzhai Member of Jurassic in the Sichuan Basin

AbstractBased on core observation, cast and fluorescent thin sections, FESEM and ESEM, coquina in Da'anzhai Member of Jurassic in Sichuan Basin were examined systematically. Together with production data and logging evaluation, a method for lacustrine coquina evaluation based on geological theory was established up. In the article, two aspects of the study were elaborated, characteristics of favorable reservoirs, and a “five‐step” evaluation method for favorable coquina reservoir. According to the correlation between porosity and production data, porosity is not effective in finding high quality coquina reservoir of this area. Whereas micro research of reservoir samples from a high productivity well revealed that sparry coquina is the best lithofacies, with the most developed micro storage space of various kinds. After the favorable reservoir was sorted out, a five‐step method evaluating the coquina reservoir was worked out. Correlation of GR value and rock types suggests that GR<30 API is an effective evaluation parameter in identifying profitable reservoir lithofacies. Meanwhile, the combination of profitable reservoir rock thickness and production data revealed that the reservoirs with the highest potentiality are those with thickness of 3–18 m. Fractures are more developed in faults, folds and structural noses in the study area. Organic acid is discharged massively before the peak of hydrocarbon generation, leading to the formation of dissolution pores in the reservoir. The evaluation of organic acid was made by using the source rock indexes. After evaluating the four factors, and compiling their distribution maps, the maps were overlapped to predict favorable reservoir zones, and 7 first class and 9 second class favorable zones of coquina were picked out.

Lithofacies characteristics and their controlling effects on reservoirs in buried hills of metamorphic rocks: A case study of late Paleozoic units in the Aryskum depression, South Turgay Basin, Kazakhstan

Metamorphic rock reservoirs are special reservoirs that are quite different from traditional sedimentary rock reservoirs and contain rich hydrocarbon reserves. However, their lithofacies characteristics and reservoir properties are relatively underexplored, and the key factor in reservoirs is lithofacies. Based on core samples, thin sections, whole-rock analysis and well-log and seismic data, we evaluated the lithologies, petrological characteristics and reservoir properties of metamorphic rocks and then explored the main factors controlling reservoir formation and metamorphic rock quality in the Aryskum depression, South Turgay Basin, Kazakhstan. In this area, four types of lithofacies are identified: granitic gneiss (high DEN and CN, low GR), leptite (high GR and CN), gabbro (low GR and CN) and granite (high GR and low CN); among these rocks, granitic gneiss is widely distributed. The reservoir spaces of metamorphic rocks are divided into fractures and pores produced via metamorphism and structural movements. Fractures can be subdivided into structural fractures (SFs), dissolution fractures (DFs), cleavage microfissures (CMfs) and microfissures (Mfs), and pores include dissolved intergranular pores (DInterPs), dissolved intragranular pores (DIntrPs) and vugs (Vgs). Numerous SFs and DFs provide the main reservoir spaces for hydrocarbons. The reservoir quality of metamorphic rocks is primarily controlled by faults, fractures, lithofacies, minerals, dissolution and paleogeomorphology. Lithofacies and minerals are the internal factors that control dissolution and fragmentation, while paleogeomorphology and faults are the external factors that control fracture development. Leptite and granitic gneiss are high-quality reservoir lithofacies, and high paleogeomorphology areas and fault zones are the optimal locations for fractures and pores. Reservoir spaces undergo a series of repeated changes from formation to development, filling and reformation, and a comprehensive reservoir evolution model is proposed to illustrate the distribution of high-quality reservoirs. This study has scientific significance for investigating the reservoir-forming mechanisms of metamorphic rocks and practical applications for exploring and developing oil and gas fields in areas with metamorphic rocks.

Heterogeneity in the overpressure zones in West Baram Delta, offshore-Sarawak, Malaysia

Geopressure prediction is crucial because all drilling programs require estimation of abnormal pressured zones. The use of rock fabric deformational relics at variable depths to determine heterogeneity in overpressure zones in reservoir has not been explored. Therefore, the aim of this paper is to use petrography to determine intrinsic variations within overpressure zones. Understanding petrographic expression of overpressure on reservoir lithofacies at variable depths will enhance the prediction of overpressure in reservoirs that are not initially logged by subsurface pressure detecting tools. Thin section and scanning electron microscopy (SEM) petrography was used to study rock fabric. The petrophysical properties of the rock samples were measured using mercury porosimetry. Two lithofacies were discretized in a single reservoir i.e., massive friable fine-grained sandstone (MFFS) (Layer 1) and massive fine-grained sandstone (MFS) (Layer 2). The underlying layer (Layer 2) is dominated by sutured quartz grains, lenticular grain orientation, quartz overgrowth and relatively low porosity and permeability. The quartz grains are polycrystalline and characterized by planar and conchoidal fractures, in contrast to the overlying MFFS layer dominated by monocrystalline and platy quartz grains. The petrographic studies show overpressure variation can be characterized intrinsically by quartz deformational features and overall texture differences.

Sequence stratigraphic analysis and reservoir quality assessment of an onshore field, Central Swamp Depobelt, Niger Delta Basin, Nigeria

Sequence stratigraphy and reservoir quality studies were carried out by integrating well logs from five wells, biofacies data, and 3-D seismic reflection data of an onshore field, Niger Delta. Nine stratigraphic bounding surfaces including five sequence boundaries (SBs) dated 13.1 through 21.8 Ma and four maximum flooding surfaces (MFSs) dated 15.9 through 20.7 Ma were delineated. Four depositional sequences were identified, with an observed upward increase in thickness. Three major stacking patterns (progradational, retrogradational, and aggradational) were delineated and interpreted as lowstand systems tract (LST), highstand systems tract (HST), and transgressive systems tract (TST) using their bounding surfaces. The main seismic facies units identified are variable amplitude facies, high-amplitude continuous facies, and chaotic facies, which were tied to corresponding well log responses. Reservoir lithofacies analysis revealed the presence of barrier bar, shoreface, tidally influenced channel, and fluvial distributary channel sands, within the three systems tracts, deposited in an overall shallow marine setting. Well correlation also showed considerable net sand reduction along depositional dip (southward) and across the strike (eastward) directions. Well log-derived petrophysical parameters such as porosity and permeability were evaluated within the context of the reservoir depositional facies. The best quality reservoirs were seen to be the TST barrier bar sands and tidally influenced channels with average porosity (ɸ) and permeability (K) values of 0.18 v/v and 542 mD and 0.24 v/v and 2215 mD respectively, while the HST shoreface and LST fluvial distributary channel sands possess average ɸ and K values of 0.16 v/v and 437 mD and 0.16 v/v and 309 mD respectively. The results establish that the major control on the differences in petrophysical properties is the primary depositional facies.

Carbonate reservoir outcrop analogues with a glance at pore-scale (Middle Jurassic, Lusitanian Basin, Portugal)

Abstract The Middle Jurassic carbonate successions from the Lusitanian Basin (Portugal) show a range of facies deposited across a ramp depositional system, well exposed over large areas. These facies are valuable for understanding reservoirs and related seal and trap configurations, namely in carbonate ramps. This paper documents primarily shallow-water units corresponding to the dominant reservoir-type facies, highlighting their potential as analogues, particularly at outcrop but integrating main macro and micro-scale characteristics. The mid and inner ramp sediments, which include the key studied units, consist of: peloidal-intraclastic, bioturbated, fossiliferous limestones; oolitic, skeletal, and coral-algal limestones, assigned to shoals and barrier-island complex; fossiliferous, oncoidal, fenestral deposits from lagoonal, peritidal and, locally, pedogenic settings; dolostones and dolomitic limestones. Facies with higher potential reservoir features are addressed in more detail, in three broad groups: sandbodies; biostromes; dolostones/dolomitic limestones. The remaining facies are more briefly described. The most widespread reservoir lithofacies are cross-stratified or massive oolitic and bioclastic grainstones to rudstones and coral-dominated biostromes. The larger-scale sandbody units show a dominant sheet-like geometry, but wedges and smaller-scale lensoid units occur, grading into, and interfingering with, other facies types. The reservoir facies are closely associated with, hence often encased by, flow baffle or barrier seal facies, either landwards (lagoonal/peritidal) or seawards (mid-outer ramp). This architecture, coupled with varied diagenetic paragenesis, created a range of stratigraphic and diagenetic traps that may be perceived as play similarities in potential exploration situations. The present reservoir quality is mostly low to moderate, but examples of high/excellent porosities and locally enhanced permeabilities occur. Overall, these units are highly suitable field analogues to clarify processes leading to depositional, diagenetic, fractured and hybrid reservoir types. Moreover, they clearly indicate how shoreface dynamics, shallow-water carbonate factory productivity and diagenesis lead to more complex reservoirs than usually appreciated in mostly homoclinal depositional systems.

Chemostratigraphy of the Upper Jurassic (Oxfordian) Smackover Formation for Little Cedar Creek and Brooklyn Fields, Alabama

The Upper Jurassic (Oxfordian Age) Smackover Formation is a significant source for hydrocarbon production in southwest Alabama. Brooklyn Field is in southeast Conecuh County, Alabama, and has been a major producer of oil and natural gas for the state. The Smackover is a carbonate formation that has been divided into seven distinct lithofacies in the Brooklyn and Little Cedar Creek fields. In southwest Alabama, the facies distribution in the Smackover Formation was influenced by paleotopography of the underlying Paleozoic rocks of the Appalachian system. The goal of this study is to determine elemental ratios in rock core within the Smackover Formation using an X-ray fluorescence (XRF) handheld scanner and to correlate these elemental characteristics to the lithofacies of the Smackover Formation in the Brooklyn and Little Cedar Creek fields. Eight wells were used for the study within Brooklyn Field and Little Cedar Creek fields. Cores from the eight wells were scanned at six-inch intervals. Chemical logs were produced to show elemental weights in relation to depth and lithofacies. The chemical signatures within producing zones were correlated to reservoir lithofacies and porosity. Aluminum, silicon, calcium, titanium, and iron were the most significant (>95% confidence level) predictors of porosity and may be related to the depositional environment and subsequent diageneses of the producing facies. The XRF data suggests relative enrichments in iron, titanium, and potassium. These elements may be related to deposition in relatively restricted marine waters.

Facies associations and depositional environments of a mixed siliciclastic-carbonate marginal marine succession: The Lower Carnian (Upper Triassic) middle Charlie Lake Formation, Kobes-Blueberry area, British Columbia, Canada

AbstractThe Upper Triassic (Carnian) Charlie Lake Formation in northeastern British Columbia, Canada is a heterolithic mixed siliciclastic-carbonate succession of dolomite dolomitic siltstone, well-sorted sandstone, bioclastic sandstone, and anhydrite. This succession is unusual in that it records the only significant non-marine interval in the Triassic of the Western Canadian Sedimentary Basin. In the Kobes-Altares-Blueberry area, moderately abundant core are available through the middle members of the Charlie Lake Formation. All available core were analyzed in order to interpret the depositional setting of constituent members and identify reservoir quality lithofacies and horizons.The middle Charlie Lake Formation in the Kobes-Altares-Blueberry area was deposited in an arid coastal setting. Sixteen lithofacies were identified and placed in three lithofacies assemblages and the latter characterize three depositional settings: coastal salina/playa, aeolian dune, and proximal marine ramps. The coastal salina/playa lithofacies assemblage is heterolithic, and is dominated by dolomitic and anhydritic facies. Depositional subenvironments include intertidal flat, ephemeral lagoon, shore proximal ephemeral lake, sabkha and supratidal paleosol. Potential reservoir lithofacies in this assemblage includes peloidal to stromatolitic dolomitic siltstone deposited in lagoonal and intertidal flat settings. The aeolian dune lithofacies assemblage preserves the movement of small, shore-proximal dunes and associated interdune successions. Well-sorted, fine-grained sandstone beds comprise the best reservoir lithofacies in this assemblage. The proximal marine ramp facies assemblage records several marine transgressions that punctuate the dominantly nonmarine/marginal marine Charlie Lake Formation. Bioclastic packstone, bioclastic sandstone and peloidal dolomitic siltstone to sandstone beds, all exhibit good porosity and are potential hydrocarbon reservoir units within this lithofacies assemblage.

A deep residual convolutional neural network for automatic lithological facies identification in Brazilian pre-salt oilfield wellbore image logs

Field characterization in oil industry is a challenging task which aims to determine or estimate some of the petrophysical properties of a reservoir. These properties are expected to be later used in a non-deterministic workflow (which might depend on subjective interpretations carried out by each petrophysicist) whose aim is to answer questions such as whether exploiting the reservoir is feasible or not, how much hydrocarbon can be extracted from it and whether the geology of the reservoir will stand the stresses of exploitation without collapsing. Three properties stand-out amongst all the rest, as they are closely correlated to the amount of hydrocarbon present in the reservoir and also to the feasibility of its exploitation: permeability, porosity, and lithology. Obtaining reliable and robust measurements of these properties requires extracting core samples from the reservoir, which is, however, a very resource-consuming task. Hence, it is common to use other tools (such as wirelogging tools or borehole imagers) to extract several other properties from the reservoir, in an attempt to obtain information that might help experts to estimate these properties on those intervals at which no core sample could be extracted. In this context, estimating lithofacies helps petrophysicists to automatize the process of identifying the lithology of the reservoir. Previous work (Basu et al., 2002; Chai et al., 2009; Linek et al., 2007; Newberry et al., 2004; Hall et al., 1996) used a considerable amount of wirelog data and borehole image logs to induce the lithology of the reservoir. In the work presented in this paper, we introduce a new methodology for automatic reservoir lithofacies identification. Our model relies only on ultrasonic and microresistivity borehole image logs as inputs, which are characterized by a deep residual convolutional network which then infers the probability of each sample to be classified as each type of previously defined lithofacies classes. The method presented in this work was tested on a carbonate well from the Brazilian pre-salt oilfields, and it allowed us to obtain an average classification accuracy of 81.45% and an average area under the ROC curve of 92.70% for all classes, for the blind test sample.