Journal of Petroleum Exploration and Production Technology最新文献

The present work aims to provide a tectonostratigraphic model of the Miocene carbonate reservoirs accumulated in Bakr-Al-Hamd ridge to help unlock an estimated statistical yet-to-find over 10 MMbbl of oil. The structural ridge is located in the western central Gulf of Suez and the hydrocarbon exploration within this NE-dipping structural high began in 1951. The model integrated several interpreted 3-D seismic volumes and their attributes, a complete set of well-log data, borehole images, and the resultant extensional structures from the natural and physical models. The structural model proposed the following: (1) a major gulf-parallel curved and faulted detachment between the two differentially strained sections of Miocene and Pre-Miocene sediments which were distinguished by seismic attributes and confirmed by borehole images, (2) the synthetic Gulf-parallel faults which represent footwall collapsing structural style of extensional faults, delineated Al Hamd Miocene Nullipore carbonate reservoir, (3) south-westward dislocation of the western gulf-parallel boundary fault of Al Hamd Nullipore facies and its allocation at the present-day shoreline, (4) three classification of the Miocene carbonate reef were interpreted; fringe reef in Bakr ridge, barrier reef in Al-Hamd, and patch reef in the intra-field. The achievements of the present study prompted exploration activity and two discoveries were announced in 2021 and 2022 in the vicinity of Bakr and Al-Hamd intra-fields. The recent discoveries penetrated more than 200 m of Miocene carbonate reef and dolomitic reservoirs accumulated on the detachment surface. The present study workflow could be used in similar petroliferous rift basins to maximize hydrocarbon resources, enhance production performance, and revive brownfields.

Drilling optimization has been broadly developed in terms of influential parameters. The assessment time and the effects of both geomechanical and drilling parameters were vital challenges of investigations. Drilling factors are applied force or rotation of drilling agents such as weight on bit (WOB), and geomechanical features represent mechanical indexes of rocks including unconfined compressive strength (UCS). Optimization efforts have been demonstrated on complex prediction methods whereas the simplicity of classification can offer some optimal ranges utilizing machine learning classifications in an accelerated process. In this study, a novel procedure using the supervised and semi-supervised learning approaches was conducted to classify and optimize the rate of penetration (ROP) and torque on bit (TOB). Firstly, in the case well, user-defined classes were assigned based on geomechanical units (GMU) and the ranges of high ROP and low TOB, thus classes divided drilling factors as GMUs of the case. Secondly, the feature selection was carried out by neural pattern recognition with three multi-objective optimization methods for classification. The inputs of classifications were WOB, hook load, pump pressure, flow rate, UCS, and internal friction angle. Classification approaches were decision trees, support vector machine (SVM), and ensemble learning. Finally, the bagged trees permutation and Laplacian SVM (LapSVM) algorithm separately revealed the significance of parameters and predicted the optimal ROP and TOB regions. Findings showed (1) in supervised classification of the case well, the cubic SVM and bagged trees had the highest area under the curve (AUC) and accuracy, on average 0.97 and 0.96, respectively. (2) The average accuracy of the supervised classifications in a test well was 91% except for the fine SVM, which makes them reliable for the fields with the least information. (3) The permutation outcomes for significant features, flow rate and UCS, exposed influential parameters for ROP and TOB optimization. (4) The semi-supervised method, LapSVM, not only acquired both ROP and TOB labels with an accuracy of 88% but also presented their optimal ranges in 95% of the assessed zones. (5) LapSVM deals with a limited training section perfectly opposed to the supervised version, which is vital for drilling investigation. (6) Implementing machine learning classification approaches with rock properties is a key factor in achieving effective drilling parameters in less time. More importantly, the recommended drilling factors concerning geomechanical properties can ameliorate both drilling performance and perception of upcoming collapse.

Unfortunately, oil reservoirs are complex considering the fluids (e.g., crude oil composition) and rock properties making it hard to propose a simple enhanced oil recovery (EOR) method for higher oil production. Besides, most of the investigations had focused on crude oil which is a complex mixture of thousands of components making it hard to extract any reliable conclusions with respect to the crude oil type. So, the current study is focused on the application of ionic liquids from different families of pyridinium and imidazolium, titanium oxide nanoparticles, and salts (MgCl₂ and CaCl₂) in the presence of resinous synthetic oil for the first time. The obtained results using the central composite design (CCD) approach revealed the positive effect of resin fraction on the IFT reduction by 27% considering the initial value (34.9%). Using the CCD approach revealed that using pH = 7, MgCl₂ concentration = 21,000 ppm, CaCl₂ concentration = 21,000 ppm, resin fraction of 9wt%t and 500 ppm of [C₁₂mim][Cl] concentration reduces the IFT to minimum value of 0.62 mN/m while the minimum IFT value for optimum conditions of solution includes [C₁₂py][Cl] led to minimum IFT value of 2.2 mN/m. But, the contact angle measurements revealed better synergy between [C₁₂py][Cl] and TiO₂-NPs (0–200 ppm) for better wettability alteration toward water-wet condition (27.3°) than [C₁₂mim][Cl] (33.2°). Moreover, the IFT measurements revealed that the presence of TiO2-NPs is effective in reducing the IFT of the optimum formulations to 0.55 and 0.84 mN/m for [C₁₂mim][Cl], and [C₁₂py][Cl], respectively. According to the results, it seems that the obtained optimum formulations for [C₁₂mim][Cl], and [C₁₂py][Cl] are applicable for EOR purposes as new hybrid solutions.

Liquid loading occurs in gas wells after a period of production, and the vortex drainage gas recovery technology can alleviate this problem by removing liquid. To substantially enhance the efficiency of this technology, a novel tool combining jetting and helical mechanisms has been introduced. To validate its effectiveness, a laboratory system for detailed analysis of pressure drops by using various tools at multiple gas flow rates has been set up. The analysis approach encompasses both single-factor and orthogonal analyses of tool structure parameters to find out the optimal tool structural parameters under different operating conditions. Consequently, a correlation between the gas flow rates observed in controlled laboratory environments and those in actual gas wells has been established. The study indicates that the tool’s main structural parameters significantly impact pressure drops along the wellbore. Furthermore, it is evident that distinct well profiles require unique tool setups to minimize such pressure drop. Field tests of the optimized tool have shown notable enhancements: The average gas flow rate increased by 25.9%, reaching 5.39 × 10⁴ m³/d (1.90 × 10⁶ scf/d), while the average liquid flow rate increased by 20.1%, reaching 1.46 m³/d (9.18 bbl/d). These results highlight the superior drainage stimulation effect of the new jetting and helical combination tool, presenting novel insights and methodologies for enhancing gas recovery in liquid-loaded gas wells.

The accuracy of predicting waterflooding performance is crucial in determining the scale of investment for oilfield development. However, existing common waterflooding prediction models often relies on assumptions that may not apply universally or lack theoretical derivation through statistical analysis. This has led to unsatisfactory prediction accuracy and multiple potential solutions. To address these limitations, it is proposed to incorporate the oil/water relative permeability ratio model into the derivation process of waterflooding prediction models. Initially, an evaluation of prevalent oil/water relative permeability ratio models is conducted, along with an analysis of their primary constraints. Additionally, the applicability of the analytical relative permeability model is thoroughly examined. Building upon the analytical relative permeability model and a modified Welge equation, a new waterflooding model is formulated, encompassing all pertinent physical coefficients. Notably, this model aligns seamlessly with the commonly used Arps’ decline curve, while extending its applicability to a broader range of conditions. Moreover, it can be simplified to generate typical water drive curves under suitable circumstances. The semi-log relationship between oil/water relative permeability ratio and water saturation is further simplified into a linear relationship or a multi-term formula. Compared with the traditional waterflooding model, the new model proposed in this research has a wider application range and can be applied to oilfield at high water cut. At the same time, the new model clarifies the coefficient of waterflooding curve A and the physical meaning of parameter 7.5 in Tong’s chart method for the first time. The new model proposed in this research further enriches the connotation of waterflooding theory and has certain application significance.

Soft rock has the properties of low strength, poor integrity, and difficulty in core extraction. In order to study the deformation and failure of soft rock, this study used fine river sand as aggregate, cement and gypsum as bonding materials, and borax as a retarder to produce cylindrical rock-like samples (RLS) with a sand cement ratio of 1:1. Uniaxial compression tests were conducted on RLS under DIT (different immersion times) (0, 4, 8, 12, 24, and 48 h) in the laboratory. The mechanical and energy properties of RLS under water-stress coupling were analyzed. The results showed that the longer the IT of the RLS, the higher their water content (WC). As the moisture time increases, the uniaxial compressive strength, elastic modulus (EM), and softening coefficient (SC) of the sample gradually decrease, while the rate of change of EM is the opposite. The fitted sample SC exhibits a good logarithmic function relationship with WC. During the loading process of the sample, more than 60% of the U (total energy absorbed) during the loading process of the sample is accumulated in the form of U_e (releasable elastic energy), while less than 40% of U is dissipated by the newly formed micro cracks during the compaction, sliding, and yield stages of the internal pores and cracks of the sample. The U before the peak and the U_e of the RLS decrease exponentially with the moisture content; the relationship curves of U_e/U (released elastic energy ratio) and U_d/U (dissipated energy ratio) of RLS during uniaxial compression with the σ₁/σ_max (axial stress ratio) can be divided into three stages of change, namely the stage of primary fissure compaction and closure (σ₁/σ_max < 0.25), continuously absorbing energy stage (0.25 < σ₁/σ_max < 0.8), and energy dissipation stage (σ₁/σ_max > 0.8); the D (damage variable) was defined by the ratio of U_d (dissipated energy) to the U_dmax (maximum dissipated energy) at failure time of RLS, the fitting of the relationship between the damage variable and axial strain conforms to the logistic equation.

The study presented in this paper has multiple objectives. First, a simulation model for partially naturally fractured reservoirs under solution gas drive is developed. The model considers the major key parameters controlling fluid flow in the reservoir, including fracture intensity and distribution, instantaneous gas/oil segregation due to vertical capillary continuity, gas/oil gravity drainage, and reinfiltration of the drained oil to the lower matrix. Once the model is well-established, it is used to study the reservoir performance under two recovery processes: primary depletion and gas injection. A detailed investigation of the sensitivity of the ultimate oil recovery to the fracture intensity, oil production rates, and gas injection rates is performed. The findings of this study indicate that the ultimate oil recovery of low-fracture intensity reservoirs subjected to the depletion drive process is insensitive to production rates. However, for moderate- to high-fracture intensity reservoirs and low production rates, the recovery increases with increasing fracture intensity. Conversely, for moderate- to high-fracture intensity reservoirs and high production rates, the recovery is not significantly affected. For the gas injection mechanism, it is found that the ultimate oil recovery is a function of both the fracture intensity and gas injection rate. Furthermore, three fracture intensity ranges are identified: low, medium, and high. For the low- and high-fracture intensity ranges, the recovery increases with increasing gas injection rates and fracture intensity. However, for the medium fracture intensity ranges, the recovery behaves differently. It increases at low gas injection rates and decreases at high injection rates as the fracture intensity increases. New equations relating the cumulative oil production to the production rates, gas injection rates, and fracture intensity are also presented.

To separate oil–water mixtures especially in oil field operations, new energy-efficient methods are urgently required. Conventional separation techniques using demulsifiers for separation of oil–water mixtures or even use of membranes usually suffered from high cost and energy consumption, composition dependency of demulsifiers and fouling or inability of a single membrane to separate all types of oil–water mixtures. This research aimed to synthesize tungsten oxide-coated stainless steel mesh using the hydrothermal method, with a focus on evaluating its effectiveness in oil–water separation. The coating procedure was carried out using hydrothermal techniques, with an emphasis on investigating the impact of precursor concentration, pH levels, reaction temperature and duration, on the separation efficiency of the optimal coating solution. The hydrothermally coated stainless steel mesh was created within a polytetrafluoroethylene reaction vessel, submerged in a 150 ml aqueous solution containing 0.0094 mol of sodium tungstate di-hydrate at pH 3.0, achieved through the addition of hydrochloric acid. Additionally, 1 g of oxalic acid, acting as a chelating agent, was introduced. Subsequently, the mesh underwent a 4 h reaction at 220 °C and was subsequently annealed for 30 min in a 350 °C furnace. Remarkably, the resultant mesh exhibited an exceptional water separation flux of 9870 ± 15 L/hr/m² when exposed to 1:1 v/v oil–water mixtures. This performance significantly outperformed previous filters designed for similar oil–water separation tasks. The mesh efficiently facilitated the passage of water through the oil–water mixture, achieving an efficiency rate exceeding 98 ± 1%. To gauge its wetting behavior, the hydrophilic/underwater oleophobic filter underwent static contact angle measurements. The filter's wetting mechanism was primarily attributed to its hierarchical surface structure, which enhanced surface hydrophilicity and roughness. Analytical techniques such as XRD, FTIR, and FE-SEM were employed to scrutinize the fabricated filter's composition. These analyses confirmed the successful creation of a nanostructured WO3 coating on both sides of the stainless steel mesh. Moreover, the utilization of commercially available chemicals and straightforward fabrication techniques underscores the promising potential of this approach for large-scale applications.

Identifying the optimal azimuth and inclination for wellbore drilling in sandy formations can be considered a valuable aid in reducing sand production risks, lost time, and decreasing drilling costs in the petroleum industry. Therefore, a numerical systematic approach was provided to predict sand production in wellbore SDX-5, drilled in a deep-water sandstone reservoir in the Shah-Deniz gas field (South Caspian Basin), which has never been done previously. Additionally, this systematic approach uses geomechanical and geodynamical criteria, along with petrophysical information (density and sonic log) and tectonic characteristics of the study area, which are influenced by the active tectonic stresses of the Apsheron-Balkhan zone. The subsurface data sources employed are more eco-friendly, available, and continuous than experimental tests. The computations conducted achieved azimuth, inclination, polar, and depth profile plots for the Lower Balakhany Formation. The calculations reveal that the optimum azimuth for the wellbore drilling trajectories is parallel to SHmax and oblique drilling to near horizontal is the result of optimum inclination. Polar plots showed optimum azimuth, inclination, and effect of wellbore trajectory on critical collapse pressure and collapse drawdown pressure with pressure values simultaneously, which identify safer alternatives for achieving higher petroleum production rates without sanding. Depth profile plots provide a simultaneous overview of the values of critical collapse pressure, critical sanding pressure for instantaneous drawdown, and optimum wellbore production pressure during drilling and production operations. Moreover, optimum reservoir fluid production (maximum discharge) rates can be identified and imposed as upper limits to prevent sand production.

The staged and layered fracturing technology plays an important role in unconventional tight reservoirs. And the gas well fracturing and completion integration is the core component to realize the fracturing and completion integration process, which can realize the integration of acid fracturing and later drainage production so as to reduce the secondary pollution to the reservoir. The packer rubber barrel’s performance directly affects the long-term effective sealing reliability itself in high temperature and high pressure environment. In this paper, the constitutive model of rubber tested from high temperature and high pressure curing kettle to simulate the high-temperature and highly corrosive environment of the formation. On this basis, the structure of the packer’s shoulder and the protective ring of the rubber barrels are optimized through Abaqus to reduce its stress failure under high pressure, and its corrosion resistance is improved by improving the rubber material. The sealing performance of the packer rubber cylinder under the field underground requirements is tested through laboratory evaluation test and field test. The results show that the protective ring and rubber tube shoulder at 30° angle are a reasonable result of optimization, and the optimized packer can meet the requirements of 154 °C temperature resistance, 79 MPa pressure bearing and long-term effective sealing. The successful development of packer rubber and the integrated analysis process can lay a solid foundation for the realization of integrated fracturing and completion process for exploration and development of deep volcanic or carbonate reservoirs.