Hydrocarbon-bearing Reservoirs Research Articles

A new approach for estimating water saturation in low-resistivity hydrocarbon-bearing reservoirs using artificial neural network (ANN)

A new approach for estimating water saturation in low-resistivity hydrocarbon-bearing reservoirs using artificial neural network (ANN)

Optimizing reservoir characterization: insights from integrated data analysis

The Onshore Hydrocarbon prospectivity of the Niger Delta X-field is examined through the integration of 3D seismic and recorded information from well log data. Probable reservoirs of hydrocarbon-bearing were delineated to tackle the non-uniqueness in the identification of hydrocarbon quantity of concern. Three significant faulting patterns or systems were delineated and their architectural attributes depict a typical Niger Delta embedded anticlinal structural pattern. The study field exhibited both synthetic and antithetic structures, hence only fault on delineated reservoirs was used for structural modeling. All well locations were sited within the fault-supported synthetic and anticlinal structures and the static characteristics within the well coordinates were analyzed through petrophysical assessment. Depicted reservoir sands show low gamma ray readings, low volume of shale, considerate hydrocarbon saturation and low water saturation. The established petrophysical models showed a better net-to-gross (NTG) ratio, for the entire delineated reservoir units. This has contributed to the assessment of hydrocarbon-bearing reservoir units before employing the strategy for field development scenario, in order to eliminate dry hole drilling campaign. These will contribute to the reduction of operational costs, having delineated the accurate geometry and petrophysical model of hydrocarbon reservoir units.

High resolution 3-D seismic and sequence stratigraphy for reservoir prediction in ‘Stephi’ field, offshore Niger Delta, Nigeria

The Offshore Niger Delta, Nigeria, stands as a dynamic geological marvel, known for its intricate processes and extensive hydrocarbon reservoirs. This study employed an integrated approach, utilizing 3D seismic data and well logs, to conduct a thorough analysis of sequence stratigraphy and reservoir characterization in the pursuit of optimizing hydrocarbon exploration in the region. The study focused on the NW–SE trending Miocene depocenters, which predominantly comprises alternating sandstone and thick shale layers within the Agbada Formation. These reservoir units showcased stacked shallow marine fluvial–deltaic sediments, separated by significant marine shale units. Within the study area, two hydrocarbon-bearing reservoirs were identified and named: R1 and R2. Petrophysical analysis identified R2 as the most promising reservoir, with a permeability of 1184 × 10− 3 µm2, 85% hydrocarbon saturation, porosity of 0.30, and effective porosity of 0.27. Fault structural analysis uncovered that hydrocarbons are trapped within a network of growth faults within the wave-dominated Niger Delta depositional system. From the sequence stratigraphic interpretation, four depositional sequences were delineated between the depths of 2030–3417 m, and are bounded by five sequence boundaries. Integrated seismic facies analysis revealed high-energy feeder systems likely supplying sediments from river sources to offshore locations. These integrated findings provide essential insights to inform resource management, exploration strategies, understanding of reservoir distribution, and structural intricacies within the complex offshore Niger Delta, Nigeria, providing valuable information. The depositional environment helped in the understanding of the stratigraphic traps which are prospects in the study area. This together with the associated reservoir quality allowed accurate prediction for potential reservoir facies and will further improve the field development plans.

Depth dimension in seepage detection: Insights for exploration and geological gas storage surveillance

The search for surface hydrocarbon seeps has historically served as a fundamental tool in the early stages of oil and gas exploration. However, as easily detectable surface hydrocarbon seeps become increasingly scarce, advancement in analytical capabilities have shifted the focus towards detecting ultra-trace levels of hydrocarbons, commonly referred to as microseepages. While it is critical to understand the distribution of hydrocarbon microseepage for assessing petroleum systems and optimizing exploration efforts, the role of sampling depth in the detection of microseepage remains poorly understood. In this study, we investigated the influence of sampling depth on microseepage detection, using passive soil-gas sampling techniques at depths ranging from 0.5 to 10 m at sites with hydrocarbon-bearing reservoirs and dry wells. Organic geochemical analysis, including thermal desorption-gas chromatography-mass spectrometry (GC-MS), was employed to identify and quantify hydrocarbon and nonhydrocarbon compounds.The study result demonstrates that sampling at the Minimal Interference Zone (MIZ) depths of 5 m or greater significantly mitigates the risk of interference signals, thereby enabling the identification and quantification of hydrocarbon microseepages at trace and ultra-trace concentrations. At these depths, the attenuation of non-hydrocarbon compounds was observed, making the hydrocarbon signal markedly more distinguishable. Geochemical characterization of the samples revealed spatial and vertical heterogeneity in the distribution of hydrocarbon compounds, indicative of variations in the microseepage mechanisms potentially influenced by factors such as sedimentary basin settings and secondary alterations associated with the vadose zone. By utilizing passive soil-gas sampling techniques coupled with GC-MS, this study emphasizes the importance of sampling depth to improve the detection of reliable microseepage signal while reducing interference and background noise. The proposed technique not only refines existing methodologies for petroleum system assessments but also paves the way for broader geological applications. Specifically, the approach offers critical insights for the development of high-resolution geochemical surveys adaptable for surface background profiling in CO2 sequestration projects to monitor for storage efficiency and seal integrity.

Evaluation of the Lower Cretaceous Alam El Bueib Sandstone reservoirs in Shushan Basin, Egypt – Implications for tight hydrocarbon reservoir potential

This study presents the evaluation of the potential reservoir intervals in the early Cretaceous Alam El Bueib Formation of the Shushan Basin, Western Desert. Seismic 2D lines, and wireline logs (including image logs) were assessed to characterize the potential intervals. The study area is characterized by E-W to ENE-WSW striking parallel sets of steeply dipping normal faults. Based on the breakouts on image log, the regional maximum horizontal stress orientation is inferred as NE-SW. The AEB Formation, as observed on the image log, consists of massive sandstones, planar laminated siltstones, sandstone-siltstone heteroliths and laminated shales, deposited in a fluvial depositional environment. The bedding planes are WNW-ESE striking with a mean true dip of NNE (around 10°). Wireline log based quantitative petrophysical assessment identified multiple promising hydrocarbon-bearing reservoir intervals within the AEB Formation. The potential reservoir intervals are clean with shale content <10% with water saturation <50%. However, all these intervals are tight with effective porosity between 4 and 12%, dominantly ∼5%. Such tight effective porosity can be contributed by extensive silica cementation in the AEB Formation, as seen from the nearby fields in Western Desert. High porosity zones are observed to be water-bearing. The wells drilled in the north and northeastern area exhibit a cumulative net pay thickness between 70 and 150 ft, while south-southeastern region exhibits a very low cumulative net pay of 10–30 ft. Based on the breakout son image log, the regional minimum horizontal stress orientation is inferred as NW-SE, which can be preferred azimuth for placing highly deviated or horizontal wells to exploit such tight clastic reservoirs by optimizing hydraulic fracture propagation. The formation evaluation presented in this work shed critical insights into the tight hydrocarbon reservoir potential of the early Cretaceous AEB.

On the efficient non-linear solver for hydraulic fracturing and well cementing simulations based on Anderson acceleration

The aim of this study is to create a fast and stable iterative technique for numerical solution of a quasi-linear elliptic pressure equation. We developed a modified version of the Anderson acceleration (AA) algorithm to fixed-point (FP) iteration method. It computes the approximation to the solutions at each iteration based on the history of vectors in extended space, which includes the vector of unknowns, the discrete form of the operator, and the equation's right-hand side. Several constraints are applied to AA algorithm, including a limitation of the time step variation during the iteration process, which allows switching to the base FP iterations to maintain convergence. Compared to the base FP algorithm, the improved version of the AA algorithm enables a reliable and rapid convergence of the iterative solution for the quasi-linear elliptic pressure equation describing the flow of particle-laden yield-stress fluids in a narrow channel during hydraulic fracturing, a key technology for stimulating hydrocarbon-bearing reservoirs. In particular, the proposed AA algorithm allows for faster computations and resolution of unyielding zones in hydraulic fractures that cannot be calculated using the FP algorithm. The quasi-linear elliptic pressure equation under consideration describes various physical processes, such as the displacement of fluids with viscoplastic rheology in a narrow cylindrical annulus during well cementing, the displacement of cross-linked gel in a proppant pack filling hydraulic fractures during the early stage of well production (fracture flowback), and multiphase filtration in a rock formation. We estimate computational complexity of the developed algorithm as compared to Jacobian-based algorithms and show that the performance of the former one is higher in modelling of flows of viscoplastic fluids. We believe that the developed algorithm is a useful numerical tool that can be implemented in commercial simulators to obtain fast and converged solutions to the non-linear problems described above.

Multi-task learning for seismic elastic parameter inversion with the lateral constraint of angle-gather difference

Pre-stack seismic inversion is an effective way to investigate the characteristics of hydrocarbon-bearing reservoirs. Multi-parameter application is the key to identifying reservoir lithology and fluid in pre-stack inversion. However, multi-parameter inversion may bring coupling effects on the parameters and destabilize the inversion. In addition, the lateral recognition accuracy of geological structures receives great attention. To address these challenges, a multi-task learning network considering the angle-gather difference is proposed in this work. The deep learning network is usually assumed as a black box and it is unclear what it can learn. However, the introduction of angle-gather difference can force the deep learning network to focus on the lateral differences, thus improving the lateral accuracy of the prediction profile. The proposed deep learning network includes input and output blocks. First, angle gathers and the angle-gather difference are fed into two separate input blocks with ResNet architecture and Unet architecture, respectively. Then, three elastic parameters, including P- and S-wave velocities and density, are simultaneously predicted based on the idea of multi-task learning by using three separate output blocks with the same convolutional network layers. Experimental and field data tests demonstrate the effectiveness of the proposed method in improving the prediction accuracy of seismic elastic parameters.

Sedimentary facies analysis of a thin-bed-dominated turbidite succession in the Miocene Temburong Formation, Kampung Bebuloh, Labuan Island, Malaysia

Thin-bedded turbidites are important hydrocarbon-bearing reservoirs in many mature fields throughout the world. The type of turbidite depositional setting strongly influences vertical and horizontal continuity of the reservoir. However, distinguishing between lobe and levee associated thin-bedded turbidites remains challenging due to their generally similar facies characteristics. This study aims to contribute some insights to this problem by conducting a detailed bed-scale facies analysis on the Early Miocene Temburong Formation exposed at Kampung Bebuloh, Labuan Island, Malaysia, which may uncover features that can help in differentiating between both depositional types. Six facies are recognized in the Temburong Formation, which are interpreted as low density turbidites (F1–F4), hybrid event beds (F5), and sustained turbidites (F6). Detailed facies and ichnology analysis reveal features which are consistent with a lobe fringe deposit rather than levee-associated environment interpretation, including tabular bed geometries, presence of hybrid event beds, and the absence of thick-bedded channel-fill sandstones. Five facies associations are identified and interpreted as representing sub-environments within an overall lobe depositional setting. A diverse trace fossil assemblage, comprising the Nereites ichnofacies is consistent with a deep marine environment. Further identification of the Paleodictyon and Nereites sub-ichnofacies indicates a distal turbidite system setting, most likely lobe fringe. Based on the thick accumulation of FA2 and FA3 and no distinct observable vertical trend, the Early Miocene Temburong Formation in Labuan is interpreted as turbidites deposited at the fringes of lobe complexes rather than a single lobe fringe. Earlier works into the Temburong Formation in SW Labuan proposed a middle slope to proximal basin floor setting where the thin-bedded intervals were interpreted as potentially representing either levee deposits or the fringes of confined lobe deposits. Conversely, the Temburong Formation at Kampung Bebuloh exhibits characteristics of an unconfined lobe setting, suggesting an evolutionary change in depositional conditions over time.

Hydrothermal alteration mechanisms of an Archaean metamorphic buried hill and the models for reservoir zonation, Bozhong depression, Bohai Bay Basin, China

Multiple metamorphic buried-hill hydrocarbon reservoirs have been recently discovered in the Bozhong Depression, Bohai Bay Basin. Among them, the buried-hill reservoirs in the BZ13, BZ19 and BZ26 regions have the largest condensate gas reserve in eastern China. The hydrocarbon-bearing reservoir has a large thickness with a maximum of ∼1 km, making the oil-equivalent reserve exceed 5 × 108 tons. This study used petrography, isotopes, gas composition, zircon U–Pb geochronology, X-ray diffraction, electronic probe and hydrothermal dissolution experiments to discuss the formation mechanisms of the metamorphic buried-hill reservoirs. The results indicate that the reservoirs 500 m below the surface of the buried hill have been significantly altered by the mantle-derived CO2. This is supported by the carbon isotope of CO2, He isotope of the helium gas, strong negative excursions in δ18OPDB, positive excursions in δ13CPDB, Co/Ni ratio greater than 1 in pyrite and secondary characteristic minerals such as dawsonite. Hydrothermal dissolution experiments using CO2 result in the precipitation of kaolinite, ankerite and quartz cements, which is consistent with petrographic observation. The mantle-derived CO2 reacts with feldspars, hornblende, biotite and carbonates, creates secondary dissolution pores and significantly improves reservoir quality. Moreover, partial carbonate cements exhibit negative excursions in δ13CPDB and the depletion of light rare earth elements, indicating the influence of organic acids-bearing low-temperature hydrothermal fluids. Therefore, three development models illustrating the formation of metamorphic buried-hill reservoirs were proposed. This study may serve as a reference for the hydrocarbon exploration in metamorphic buried-hill reservoirs.

The experimental and numerical analysis of elastic rock mechanical properties in tight conglomerate rock samples: a case study in Junggar Basin

Tight conglomerate rocks consist of gravels and rock matrices. The existence of these stiff gravels leads to heterogeneity in conglomerates and makes it difficult to characterize rock mechanical properties, which then affects drilling and hydraulic fracturing operations in tight conglomerate hydrocarbon-bearing reservoirs. This case study introduces a series of experimental and numerical analyses for the better understanding of rock deformation and elastic wave propagation patterns in a tight conglomerate reservoir in Junggar Basin, China. Tri-axial compression tests, acoustic test, and finite element modeling of rock deformation and elastic wave propagation in conglomerate rocks are presented. Experimentally tested samples exhibit good brittleness and shearing failure patterns, while well correlated static-dynamic elastic moduli and P-S wave velocities are captured. Numerical results show that the existence of stiff gravels leads to strong direction-dependent stress and strain anisotropies. Stress concentrations are also induced by gravels radially and axially. In the elastic wave domain, stiff gravels facilitate the propagation of elastic waves. The gravel close to the wave source also induces stronger compressive/tensile states in the wave domain, indicating that the existence of gravels in conglomerates can alter waveforms. This integrated approach improves the quantitative understanding of stress, strain, and elastic wave responses in heterogeneous tight conglomerates. This case study also serves as a reference for the brittleness evaluation and geomechanical evaluation in the study area. The contribution of this work is primarily about the integrated experimental study, solid deformation modeling, and elastic wave modeling of tight conglomerate rocks.

Complex spherical-wave seismic inversion in anelastic media for the P-wave minimum quality factor

Attenuation always exists when seismic waves propagate in underground anelastic media, especially in hydrocarbon-bearing reservoirs. Quality factor Q or attenuation factor 1/ Q can be used to quantify the seismic wave attenuation and has become an important hydrocarbon indicator. The relationship between the plane-wave reflection coefficient ([Formula: see text]) in anelastic media and P- and S-wave quality factors has been widely used in the plane-wave seismic inversion to estimate the quality factors. The [Formula: see text] provides an adequate approximation for the deeper subsurface. However, for the shallow subsurface and anelastic wavefields excited by point sources, the [Formula: see text] is inaccurate and its meaning involves some fundamental difficulties. In view of this, a Q-dependent P-P spherical-wave reflection coefficient ([Formula: see text]) in anelastic media is used here. Considering that having too many parameters to be inverted will lead to unstable and inaccurate inversion results, we further derive an approximate anelastic [Formula: see text] and anelastic spherical-wave impedance ([Formula: see text]), which are frequency dependent and are the functions of P- and S-wave velocities, density, and P-wave minimum quality factor ([Formula: see text]). Finally, a complex spherical-wave seismic inversion approach in anelastic media for the P-wave minimum quality factor is developed. Using the Bayesian inversion approach and complex convolution model, we first estimate the multilayer [Formula: see text] from the complex seismic traces with different frequencies and incidence angles. Based on the inverted angle- and frequency-dependent [Formula: see text], the P- and S-wave velocities, density, and P-wave minimum quality factor are further estimated using a nonlinear inversion tool. Synthetic examples verify the feasibility and robustness of the complex spherical-wave seismic inversion approach in anelastic media. In the shallow subsurface, the spherical-wave inversion is superior to plane-wave inversion. A field example further demonstrates the accuracy and great potential of our approach in hydrocarbon-bearing reservoir prediction.

A new nuclear magnetic resonance-based permeability model based on two pore structure characterization methods for complex pore structure rocks: Permeability assessment in Nanpu Sag, China

The nuclear magnetic resonance (NMR) estimate of permeability is a fundamental method that has numerous applications in reservoir engineering and petrophysics. To improve the accuracy of the NMR-based permeability model, many variables are introduced into NMR-based permeability prediction models due to geometric complexity and pore structure heterogeneity. In this paper, two pore structure characterization methods are investigated based on the Kozeny-Carman model and equivalent component model. Furthermore, an NMR-based permeability model accounting for the effect of pore structure is developed based on the analysis of the relationship between two pore structure parameters, and it is applied to practically predict permeability. Results indicate that the new model-calculated permeability has good agreement with experimental data; moreover, the adaptability of the new NMR-based permeability prediction model is highly improved through reducing undetermined variables, and key parameters can be measured directly using NMR. The new model provides a valuable scientific resource and assists in the evaluation of hydrocarbon-bearing reservoirs with complex pore structure, such as tight sandstone, shale, and carbonate rock.

Identification of challenging gas-bearing reservoir based on machine learning (ML) and computed conversion-based AVO analysis: a study from Jaisalmer Sub-basin, India

Amplitude variation with offset (AVO) analysis is an important tool for identifying natural gas-bearing reservoirs. The changes in seismic amplitudes based on the variation of density and velocity of the rock matrix are captured through the AVO analysis. The current work was performed in the Ghotaru region of the Jaisalmer Sub-basin area, where limited and discrete hydrocarbon discoveries were observed from the Lower Goru Formation during the earlier various exploration campaigns. The discrete nature of the reservoir lithofacies developed challenging scenarios for the successful exploratory campaign. The campaign encountered more difficulties because of limited advanced datasets, which affected the study to capture the extension of hydrocarbon-bearing reservoir lithofacies and its characterization towards a successful exploration campaign. This study shows the way to overcome these challenges using an existing conventional dataset. The study shows the possibility of AVO analysis using a post-stack seismic dataset. A unique conversion method from post-stack to pre-stack seismic is introduced in this study based on the uses of the integrated velocity model. An integrated, robust velocity model was developed with consideration of anisotropy factors. Introducing a machine learning-based algorithm in the petrophysical study, including the conventional approach, provides a robust validation of this work. Intercept (A) and gradient (B) are the basic outcome of AVO analysis. The well-based study and AVO analysis based on intercept (A) and gradient (B) complement each other for finding hydrocarbon-bearing reservoir rock. Cross-plots and AVO analysis show the reservoir's lithofacies extension and fluids. The study reveals the potential of natural gas retained in the Lower Goru Formation, which is composed of patchy sandstone. Two AVO classes (Class I and Class III) of gas-bearing sandstone have been identified in this study. This study presents a unique method for identifying natural gas reservoirs with limited old conventional data.

Study Reviews Largest ASP Project From Laboratory to Pilots and Field Application

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 215058, “A Systematic Review of the Largest ASP Flood Project in the World: From Laboratory to Pilots and Field Application,” by Yunan Wei, SPE, Xiaoguang Lu, SPE, and Jianhong Xu, SPE, C&amp;C Reservoirs, et al. The paper has not been peer reviewed. _ The complete paper presents a systematic review of the largest alkaline-surfactant-polymer (ASP) flood project in the world, applied in the largest oil field in China. First, reservoir and fluid characteristics are highlighted to understand heterogeneity of the reservoir. Next, project history is summarized, including laboratory studies, pilot tests, industrial-scale tests, and fieldwide application. Finally, typical ASP flood performance and reservoir management measures from over 30 years of experience are presented. Performances of ASP flood and polymer floods in the same field also are compared.​​​​ Introduction In the La-Sa-Xing Field, ASP flooding was studied in the laboratory from 1987 to 1993 and followed by five small-scale pilots from 1994 to 1999, all successfully achieving incremental recoveries of approximately 20% stock-tank oil initially in place (STOIIP). As a result, industrial-scale pilots were conducted from 2000 to 2007, resulting in increased production by ASP flooding from 3,887 to greater than 19,000 BOPD in 2007. Fieldwide ASP expansion was launched in December 2007. By 2021, the ASP-flooded blocks registered a STOIIP of 1.9823 billion bbl. Daily production was approximately 96,000 BOPD through approximately 9,650 wells. Average incremental recovery factor was 20% STOIIP with waterflooding and 8% with polymer flooding, providing an ultimate recovery factor of 60%. Cumulative oil production by ASP flooding had reached 316 million bbl by 2021, making it the largest ASP flooding project in the world. Geological Background and Reservoir Characteristics The La-Sa-Xing Field is in the north of the Songliao Basin of northeast China, comprising the majority of the Daqing field complex. The field was placed onstream in 1960. The hydrocarbon-bearing reservoir has a gross thickness of 1,377 ft and a net thickness of 394 ft. Net pay averages 150 ft. Initial reservoir pressure ranges from 1,523 to 2,585 psi. Reservoir temperature varies from 113 to 122°F. Crude oil has an API gravity of 33°, a viscosity of 8.5–10.3 cp at reservoir conditions, an initial gas/oil ratio of 258 scf/STB, and a bubblepoint pressure of 1,291 psi. Formation water salinity is 7000 mg/L. Reservoir rock initially shows water or weak oil wettability. Depending on permeability, three types of reservoir sand (Type I, Type II, and Type III) have been identified. Currently, ASP flooding is mainly applied to Type I sand, with partial application to Type II Sand.

Petrophysical Evaluation and Seismic Interpretation of Geowil Hydrocarbon Bearing Reservoir in the Niger Delta Region of Nigeria

Petrophysical Evaluation and Seismic Interpretation of Geowil Hydrocarbon Bearing Reservoir in the Niger Delta Region of Nigeria

Retrofitted Autonomous Inflow Control Devices Optimize Completions Design

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper OTC 31301, “Optimized Completions Design Using Retrofit Autonomous Inflow Control Devices,” by Ezinne A. Nnebocha, Schlumberger; Akinola Akinbola, NPDC; and Omagbemi G. Kayakor, First Hydrocarbon Nigeria, et al. The paper has not been peer reviewed. Copyright 2021 Offshore Technology Conference. Reproduced by permission. _ Discovered in 1964, the Beta Field in the Niger Delta sedimentary basin consists of 25 stacked hydrocarbon-bearing reservoirs between 5,500 and 12,000 ft true vertical depth subsea (TVDSS). Oil production peaked at 8,900 STB/D shortly after field startup and has been on the decline. Two horizontal wells, Beta 7 and Beta 8, were planned in the field, but a production forecast of the planned wells showed potential early water breakthrough and high water cut. Autonomous inflow control devices (AICDs) were deployed successfully in the Beta Field for the purpose of minimizing water production and maximizing oil recovery. Introduction After history matching, the two new horizontal wells were simulated to target the sweet spots in the reservoir using constraints of oil saturation, porosity and permeability limits, and distance to the oil/water contact (OWC). The history-matched model was then used in forecasting the production profile for the new wells using a target liquid production rate of 2,000 STB/D. The production forecast without inflow control showed water breakthrough in the new wells within the first month of production, reaching to 45% within 3 months of production. Cyclonic AICD completions then were simulated for Beta-7 and Beta-8 horizontal wells, which showed improved oil production and delayed water production. AICD Retrofit Design Cyclonic AICDs were selected for application in the Beta Field to improve production performance. However, the short lead time required for the job execution and border closures caused by the COVID-19 pandemic created restrictions in mobilizing personnel and equipment from outside the country. It did not appear that the equipment could arrive in time for the job. The conventional nozzle-based passive ICD joints were available in country. Therefore, leveraging engineering skills and operational knowledge, a solution to retrofit AICD nozzles in existing ICD screen joints was conceived. The engineering team developed a design of machined components that could be quickly manufactured at the facility of the original equipment manufacturer (OEM) and shipped to the location. Failure-mode and effects-analysis assessment, and subsequent risk-management procedures, became useful to manage the process locally with the help of the remote OEM team. A step-by-step procedure on the retrofit was devised. Fig. 1 shows a flow chart used to guide the retrofitting process and the retrofitted AICD joints after modification. Upon completion of the screen retrofit, the joints were quality-checked and inspected to verify their preparedness for well completion.

Origin of CO2 in Upper Devonian Duperow Formation and the Bakken Petroleum System at Kevin Dome, Northwest Montana

Carbon capture and storage (CCS) is a key mitigation strategy in achieving global net-zero emissions. It is therefore essential to identify and characterize potential subsurface storage repositories. Natural CO2 accumulations provide an opportunity to understand the behavior of CO2 in the subsurface. Here, we investigate the source(s), migration, and storage of CO2 in the Upper Devonian Duperow Formation at Kevin Dome, northwest Montana, USA within the Bakken Petroleum System. We report, major gas, stable and noble gas isotopic compositions in bulk gas samples (n = 19) produced from nearby hydrocarbon-bearing reservoirs at Kevin Dome and compare with CO2 bearing fluid inclusions (n = 24) from the Duperow Formation. Using the same methods, bulk gas samples (n = 9) from the adjacent Ferguson Field, (Exshaw/Bakken Petroleum System) in southern Alberta, Canada, and fluid inclusions from the Sweetgrass Hills igneous complex (n = 2) were analyzed to understand CO2 generation and the subsequent processes affecting CO2 regionally. We find that CO2 in the Upper Devonian Duperow Formation is magmatic in origin, likely related to the nearby Sweetgrass Hills igneous complex intrusion (∼52 Ma), whereas CH4 and N2 gases are generated predominantly by thermogenic processes associated with hydrocarbon generation during burial. Since emplacement, most CO2 in the hydrocarbon-bearing reservoirs of the Bakken petroleum system at Kevin Dome (∼98%) and the Ferguson Field (∼82%) has subsequently been dissolved into the groundwater. We employ a solubility model to calculate minimum gas/water ratios in Kevin Dome and the Ferguson Field, which are consistent with more groundwater interaction and more dissolution at Kevin Dome. Understanding the subsurface processes affecting CO2 is critical for future CO2 storage site selection.

LOW RESISTIVITY PAY DEVELOPMENT: CASE STUDY OF TALANGAKAR FORMATION ASRI BASIN, OFFSHORE SOUTHEAST SUMATRA, INDONESIA

Southeast Sumatra is a prolific oil and gas block located offshore in the Java Sea, 90 km north of Jakarta Bay. This area covers two major basins, namely Sunda Basin and Asri Basin. The initial development of the area focused on faulted and high closures and high-resistivity reservoirs. Further analysis shows that there are special low-resistivity reservoirs in Widuri Area, especially in the Aryani field. This paper will discuss the low resistivity pay zone reservoirs and fluid containment of the intervals. The paper will also include further assesment this undeveloped interval to increase oil production, considering the upside potential of the reservoirs using current geological, geophysical, and reservoir engineering approaches. Additionally, it will describe the operational challenges faced during the production period. The low-resistivity pay zone, a hydrocarbon-bearing reservoir in the Aryani field of the Widuri area, was identified using gas readings in the daily drilling reports, complemented with mud logging data. The Basal Sand interval, which drapes above the basement, was the site of the first producing well of Basal Sand, Aryani AC-X, preceded by a hydraulic fracturing job. Lambda-mu-rho inversion was implemented to delineate this reservoir. To recognize the potency in those wells, data reconfirmation was conducted between the elan summary, sidewall core, and cutting data. Aryani AC-X has successfully drained oil using a submersible pump, with an initial production of 408 bopd and cumulative production of 240 MBO.

Gas channel delineation utilizing a neural network and 3D seismic attributes: Simian Field, offshore Nile Delta, Egypt

Depositional architecture and hydrocarbon-bearing reservoir detection are considered the main challenges in the Nile Delta Basin, predominantly in the slope area. Channel fill deposits are very complicated because they are vertically stacked and pass through different depositional stages, forming complex depositional patterns. In the current study, an artificial neural network was used to detect gas and water-bearing reservoirs inside the complex depositional pattern and their spatial dimensions. Modern seismic reservoir characterization attribute analysis provides a good outcome in detecting reservoir fluids by mixing fluid-sensitive attributes with the well outcomes. Artificial Neural Network (ANN) algorithms for rock property prediction are considered to be a new emerging trend. The ANN algorithm has an advantage over other seismic reservoir delineation techniques because it has a good capability for building a nonlinear relationship between seismic data and petrophysical logs.Hence, it can be utilized to spatially anticipate reservoir fluids with a rational degree of accuracy. A back-error propagation algorithm, a supervised neural network method, was implemented on the Simian Field to anticipate the fluid-bearing reservoirs from the seismic-derived amplitudes. The ANN method showed unique results in the case study area by discriminating the gas-bearing intervals from the water-bearing intervals, although combining the assembly of the seismic attributes to supervise fluid classification. The method will help in the development plans of the field and track the volume of water and gas.

Petrophysical properties and volume estimation of hydrocarbon resources in x field, onshore niger delta: A reservoir characterization study

A reservoir characterization study was conducted on three wells located in X Field, situated in the Onshore region of the Niger Delta. A suite of conventional digital well logs was utilized to identify hydrocarbon-bearing reservoirs, determine reservoir petrophysical parameters, and infer the depositional environment. The study delineated four hydrocarbon-bearing reservoirs, labeled A, B, C, and D, with porosity estimates ranging from 25% to 27%, and permeability values varying from 1863.22md to 2759.78md. These results suggest that the reservoirs have good storage capacity and permit free flow of fluids, consistent with prior research in the Niger Delta. The water saturation values, ranging from 43% to 70% for Well X and 53% to 94% for Well Y, indicate the presence of significant hydrocarbon in reservoir C, while Well Z did not contain any hydrocarbon. The estimation of oil and gas resources indicated that Well X contains 1.11 X 105 barrels/acre of oil and 5.16 X 107 cubic feet/acre of gas, while Well Y contains 4.43 X 106 cubic feet of gas. The analysis of the volume of shale (0.15-0.19) revealed that the reservoirs range from slightly shaly sand to shaly sand. Based on the log motifs, the study suggests that the reservoirs are mainly fluvial channel deposits, and the rapid alternation of thin beds of sand and shale indicates deposits of delta progradation and river floodplain deposits.