The energy resources mainly petroleum and petroleum hydrocarbons are major pollutants of the environment. The oil and oil products contamination may cause severe harm and hence, the attention has been remunerated in the development of alternative technologies for elimination of these contaminants. Biosurfactants were used in the remediation of oil pollution due to advantages such as biodegradability and low toxicity. The biosurfactants are produced from low cost substrates like agro-industrial wastes which reduce the cost of production. Biosurfactants and bioemulsifiers are amphiphilic compounds and are produced as extracellular or a part of the cell membrane by bacteria. The insight view, how hydrocarbons are degraded by microorganisms and thereby reduce the damage of ecosystem is highly essential to target the problem. Biofilms are the bacterial communities which protects the bacterial cells from various adverse conditions. The present review describes the biosurfactants and its synthesis from bacteria and also emphases on the role of surfactants in oil remediation.

The Messinian sequence in the Nile Delta hosts the most prolific hydrocarbon reservoirs, and is therefore of great importance from the aspect of nonrenewable fuel sources exploration and development strategies. This study presents an investigation for the differential impacts of the depositional and petrophysical attributes on the hydrocarbon volumes trapped in the Messinian reservoirs. Analyses of the pressure data and pressure gradients revealed hydraulically-connected and homogeneous Messinian reservoir rocks. The amounts of Stock Tank Oil and Gas Initially In Places (STOIPP & GIIP) are typically controlled by the depositional primary attributes (matrix content and grain size) which induce several reservoir heterogeneities. The Lower Messinian Qawasim reservoir is subdivided into two main zones: the distal deltaic (zone 1) prograded into proximal deltaic facies (zone 2). The petrophysical reservoir quality in terms of porosity, permeability and water saturation increases upward from zone 1 to zone 2. These are largely controlled by the depositional attributes, and therefore zone 2 with a minimum matrix content, coarse-grained sandstones and mega pore spaces (>150 μm) hosts almost 90% of the STOIIP and 100% of the GIIP. Notably, approximately 78% and 65% of the total STOIIP and GIIP, respectively are confined within the coarse-grained delta-plain distributary channels of zone 2. Similarly, the fluvial sediments (zone 1) of the Upper Messinian Abu Madi Formation host 78% of the GIIP in West Al-Khilala Field and the other 22% is trapped in the overlying zone 2 and is mostly distributed within the sand-prone tidal channel and tidal sand bars facies. The channel width/thickness (W/T) ratio largely controls the STOIIP and GIIP values. STOIIP and GIIP display a progressive linear increase with increasing the channel width. This is likely due to increasing the percentage of the good reservoir quality facies within the geologic model as well as increasing the reservoir connectivity with increasing the channel width.

Capillary pressure curve plays a critical role in the reservoir evaluation. It is essential to reconstruct and predict capillary pressure curve properly. Many traditional capillary pressure correlations have been suggested in the literature. However, their major limitation is mainly applicable to homogenous reservoir, and the larger error will be caused when heterogeneous reservoir is dealt by using these mathematical correlations. This study aims at providing an important method based on Particle Swarm Optimization-Back Propagation Neural Network (PSO-BP neural network) to represent and predict capillary pressure curve for homogenous and heterogeneous reservoir. The combination of PSO algorithm and BP neural network converges quickly, which improves the accuracy and efficiency of simulation. In this paper, core samples from three blocks of the same marine-sand reservoir, whose porosity is between 0.6% and 20.0% and permeability is between 0.1mD and 6117mD, are investigated by PSO-BP neural network method and J-Function method respectively. The reconstruction and prediction results are compared with the results obtained by mercury intrusion method in laboratory. The results show that capillary pressure curves reconstructed and predicted by PSO-BP neural network method are in better agreement with mercury intrusion curves than J-Function method, with 0.1%-5% and 5%-8% relative error respectively, which can totally meet the in-situ requirements. It is also demonstrated that PSO-BP neural network method is more suitable for homogenous and heterogeneous reservoir.

Bubble point pressure is one of the most important pressure-volume-temperature properties of crude oil, and it plays an important role in reservoir and production engineering calculations. It can be precisely determined experimentally. Although, experimental methods present valid and reliable results, they are expensive, time-consuming, and require much care when taking test samples. Some equations of state and empirical correlations can be used as alternative methods to estimate reservoir fluid properties (e.g., bubble point pressure); however, these methods have a number of limitations. In the present study, a novel numerical model based on artificial neural network (ANN) is proposed for the prediction of bubble point pressure as a function of solution gas-oil ratio, reservoir temperature, oil gravity (API), and gas specific gravity in petroleum systems. The model was developed and evaluated using 760 experimental data sets gathered from oil fields around the world. An optimization process was performed on networks with different structures. Based on the obtained results, a network with one hidden layer and six neurons was observed to be associated with the highest efficiency for predicting bubble point pressure. The obtained ANN model was found to be reliable for the prediction of bubble point pressure of crude oils with solution gas-oil ratios in the range of 8.61-3298.66 SCF/STB, temperatures between 74 and 341.6 °F, oil gravity values of 6-56.8 API and gas gravity values between 0.521 and 3.444. The performance of the developed model was compared against those of several well-known predictive empirical correlations using statistical and graphical error analyses. The results showed that the proposed ANN model outperforms all of the studied empirical correlations significantly and provides predictions in acceptable agreement with experimental data.

The condensate blockage causes a substantial decrease in well productivity for gas condensate reservoirs. Based on the previous studies, a novel experimental method was designed to evaluate condensate blockage and the mitigating effect of gas injection. The method considers the stacking effect in the near wellbore region and the gas flow in the far wellbore region. There is an intermediate vessel containing condensate gas at the entrance of core holder in the experimental apparatus. In the process of pressure depletion experiment in a long core model, the vessel is connected to the core and the pressure of the vessel remains above the dew point pressure. The seriousness of condensate blockage is investigated by this research. When pressure drops to maximum retrograde condensation pressure, the gas permeability decreases by 80% compared with the initial gas permeability. Contrastive experiments were conducted to study the removal effect of different injection fluids and different injection volumes. The results show that CO₂ injection is more effective than methanol in mitigating condensate blockage and the optimal CO₂ injection volume is around 0.15 HCPV.

The necessity of oil formation volume factor (B_o) determination does not need to be greatly emphasized. Different types of reservoir oil have specific conditions which impart the hydrocarbon's major properties, among which is the oil formation volume factor. Therefore, it seems imperative to construct a model capable of estimating the value of oil formation volume factor. Previous studies have resulted in a number of correlations for oil formation volume factor estimation; however, a large portion of them do not provide an acceptable accuracy (at least in some range of data) and cause a huge error at these points. Some others are not flexible enough to be tuned for a specific type of reservoir oil and a comprehensive piece of work does not exist as well in order to compare the applicability of the new models for estimating the oil formation volume factor. In this research, a model based on simulated annealing (SA) has been built in terms of temperature, solution gas-oil ratio, and gravity of oil and gas to predict the oil formation volume factor. This model is compared with the models proposed in the most recent studies, which shows the greater performance of the new method. In addition, in this paper the models of the recent years were compared with each other and their applicability were discussed. Aiming to compare the models, 420 data points were selected and the estimated values of each model for oil formation volume factor were compared with their experimental ones.

The pressure response for the composite reservoirs with a sealing fault locating in inner and outer region is different, which neglected by previous researchers, would cause significant errors during well-test interpretations. Based on seepage theory, a well-test model of two-region radial composite reservoir with infinite outer boundary has been built in this study considering wellbore storage and skin effects. The solutions for this model and characteristics of the type curves have been analyzed by applying the method of mirror image, Laplace transformation and superposition principle, including a straight fault, a perpendicular fault and parallel faults cases. The study shows that the dimensionless pressure derivative curves would be obviously different in two cases: the well to fault distance is larger, and smaller than the half length of the inner-region radius. Therefore, type curves are presented with reasonable parameters to analyze the distance effect on the dynamic pressure response. The results in this study are of great significance for guiding the oil and gas composite reservoirs' production and optimizing the hydrocarbon recovery.

Steam Assisted Gravity Drainage (SAGD) is widely used in the Athabasca oil sands deposit to recover bitumen. Since the viscosity of bitumen is high at original reservoir conditions, heat is required to lower its viscosity to the point it becomes mobile enough to be recovered under gravity drainage. To heat the reservoir, steam is injected into the formation and thus SAGD is energy intense. Given that the fuel used to generate steam is the largest operating cost, the steam-to-oil ratio is one of the key parameter for evaluating the economics of any SAGD project. Here, the use of dynamic distributed steam injection within a pad of SAGD wellpairs is explored. The results demonstrate that feedback control leads to improvements of the SOR over that of constant pressure. The results show that the controller is able to detect the “sweet spots” (oil zones with better geological properties) in the reservoir and dynamically deliver more steam to that region. Meanwhile, it reduces the steam injection towards relatively worse quality zones to lower the local SOR.

With the extensive application of polymer flooding technology in offshore oilfields, the plugging in polymer injection wells has become more and more severe, which seriously affects the oil displacement effect and regular production of oilfields. In this paper, a new kind of blockage remover has been developed and evaluated by rheological behavior experiments, dissolution experiments and core flooding experiments. The results reveal that this new blockage remover can effectively reduce the viscosity of polymer and completely degrade the reservoir blockage with low corrosion rate. It is beneficial to long-term production of oil wells in offshore oilfield. Results of core flooding experiments show that this new blockage remover can relieve polymer damage and improve permeability. The agent has been applied in LD10-1 oilfield in 2016, the daily injection rate increased significantly after stimulation.

In this study, a sandpack model with porosity and permeability of 32.3% and 9.4 D, and a heavy crude oil with viscosity of 6430 mPa.s were used to represent a typical thin heavy oil formation. First, different ratios of C₃H₈ to CH₄ stream were prepared and their performance on Cyclic Solvent Injection (CSI) method was examined to quantify the optimum solvent concentration. Second, CO₂ was introduced to the optimum quantified CH₄-C₃H₈ mixture to investigate the extent to which CSI behavior changes by partially replacement of CH₄ with CO₂.

Results showed that ultimate oil recovery factor (RF) increased from 24.3% to 33.4% original oil in place (OOIP) when C₃H₈ concentration increased from 15 to 50 mol% in the CH₄ stream. CSI tests with higher C₃H₈ concentration reached the maximum cyclic recovery with lower number of injection cycles -due to higher solubility of C₃H₈ compared with CH₄. Solvent utilization factor (SUF) data also confirmed this as lesser volume of solvent with higher C₃H₈ concentration was required to produce oil.

Visual observations showed that the produced foamy oil lasted longer with higher concentration of C₃H₈ in the solvent (5 min for 15% C₃H₈ -85% CH₄ case versus 180 min for 50% C₃H₈ -50% CH₄ case). Upon addition of CO₂ to the mixture, the solvent apparent solubility increased and foamy oil flow promoted. The highest cyclic C₃H₈-CH₄ apparent solubility of 0.175 gr. solvent/100 gr. remaining oil jumped to 0.53 gr. solvent/100 gr. remaining oil when 35% mole fraction of CO₂ replaced CH₄. The highest ultimate oil RF of 44.11% OOIP was measured from eight cycle injection of 50% C₃H₈ -15% CH₄ -35% CO₂. This solvent also benefited from the longest stability of produced-oil foamy shape with recorded time of 217 min (including production time).

According to the results of this experimental study, it seems that there is an optimum fraction of C₃H₈ in CH₄ stream injection in heavy oil systems (with viscosity in the vicinity of 6430 mPa s); the concentration beyond which ultimate oil recovery factor does not increase significantly (near 50 mol%). It is speculated that last cycles do not appreciably respond to heavy oil production mainly due to asphaltene getting precipitated within the model.

In this study, an immiscible oil-water two phase flow in a typical porous media was modeled using the well-known Lattice Boltzmann method. A set of flow tests for modeling an oil-water two phase flow in the porous media were conducted to generate the capillary pressure curves for two distinctive initial conditions, namely, water and oil dispersed conditions in two domains of different resolutions. Based on the obtained results, the general trend of these curves has an acceptable agreement with the usual trend of these curves in hydrocarbon reservoirs and the capillary data are independent of the initial conditions. Also, the results showed the effect of grid resolution on capillary data which are validated quantitatively by proposing a new approach using Purcell's equation. One can see that they are compatible with the geometrical characteristics of the porous media as well as the conditions governing the tests. Finally, another set of tests for oil water pairs of higher viscosity ratio up to 4.4 was performed in a low porosity heterogeneous porous media and the viscous coupling effect on capillary data, due to viscosity ratio, was studied to strengthen the model validation.

The fluid flow of unconsolidated sandstone reservoir can be affected by compaction and sand production which will damage the reservoir and affect oil well productivity. This study aims to measure how the two factors affect the fluid flow. Firstly, single-phase displacement test was applied to investigate how the permeability changed with compaction. Then two-phase displacement test assessed the influence of compaction on oil production. Finally, the characteristics of fluid flow with compaction and sand production were studied under different water content. The results demonstrate that the reduction of permeability with compaction is irreversible, which will result in lower productivity. In contrast, sand production can increase the permeability at mid and high water content, which slows down the decline of oil production. Generally, the oil well productivity is reduced because of compaction even with sand production, especially when the formation pressure drop varies from 2 MPa to 4 MPa. Consequently, advance water injection is necessary to keep the formation pressure and oil production during oilfield development of unconsolidated sandstone reservoir. Simultaneously, the study can provide theoretical basis and references for the similar reservoirs.