Research on the Application of Integrated Learning Models in Oilfield Production Forecasting.

Forecasting oil production is crucially important in oilfield management. Currently, multifeature-based modeling methods are widely used, but such modeling methods are not universally applicable due to the different actual conditions of oilfields in different places. In this paper, a time series forecasting method based on an integrated learning model is proposed, which combines the advantages of linearity and nonlinearity and is only concerned with the internal characteristics of the production curve itself, without considering other factors. The method includes processing the production history data using singular spectrum analysis, training the autoregressive integrated moving average model and Prophet, training the wavelet neural network, and forecasting oil production. The method is validated using historical production data from the J oilfield in China from 2011 to 2021, and compared with single models, Arps model, and mainstream time series forecasting models. The results show that in the early prediction, the difference in prediction error between the integrated learning model and other models is not obvious, but in the late prediction, the integrated model still predicts stably and the other models compared with it will show more obvious fluctuations. Therefore, the model in this article can make stable and accurate predictions.

Optimization of Gel Flooding during the High Water Cut Stage in a Conglomerate Reservoir of the Xinjiang A Oilfield.

Influenced by water injection, a dominant flow channel is easily formed in the high water cut stage of a conglomerate reservoir, resulting in the inefficient or ineffective circulation of the injected water. With gel flooding as one of the effective development methods to solve the above problems, its parameter optimization determines its final development effect, which still faces great challenges. A new optimization method for gel flooding is proposed in this paper. Firstly, the gel flooding parameters were obtained through physical experiments; then, an experimental model of gel flooding was established according to the target reservoir, and parameter sensitivity analysis was carried out. Next, a history matching of the gel flooding experiment was carried out. Finally, history matching of the target reservoir was also carried out, and a gel flooding scheme was designed and optimized to determine the best parameters. The experimental results showed that the gelation time was 4 h and the gel viscosity was 6332 mPa·s; the breakthrough pressure, resistance factor (RF), and residual resistance factor (RRF) all decreased with the increase in permeability. The gel had a good profile control ability and improved oil recovery by 16.40%. The numerical simulation results illustrated that the porosity of the high permeability layer (HPL) had the greatest impact on the cumulative oil production (COP) of the HPL, and the maximum polymer adsorption value of the HPL had the largest influence on the COP of the low permeability layer (LPL) and the water cut of both layers. Benefiting from parameter sensitivity analysis, history matching of the gel flooding experiment and a conglomerate reservoir in the Xinjiang A Oilfield with less time consumed and good quality was obtained. The optimization results of gel flooding during the high water cut stage in a conglomerate reservoir of the Xinjiang A Oilfield were as follows: the gel injection volume, injection rate, and polymer concentration were 2000 m3, 50 m3/d, and 2500 mg/L, respectively. It was predicted that the water cut would decrease by 6.90% and the oil recovery would increase by 2.44% in two years. This paper not only provides a more scientific and efficient optimization method for gel flooding in conglomerate reservoirs but also has important significance for improving the oil recovery of conglomerate reservoirs.

Optimization and characterization of biosurfactant produced by indigenous Brevibacillus borstelensis isolated from a low permeability reservoir for application in MEOR.

Biosurfactants are expected to be a key factor for microbial enhanced oil recovery (MEOR). In this study, we described the novel biosurfactant-producing strain Brevibacillus borstelensis YZ-2 isolated from a low permeability oil reservoir. We purified and characterized the biosurfactants produced by this YZ-2 strain via thin-layer chromatography and MALDI-TOF-MS, revealing them to be fengycins. We additionally used a Box-Behnken design approach to optimize fermentation conditions in order to maximize the biosurfactants production. Core flooding experiments showed that biosurfactants produced by YZ-2 can significantly enhance crude oil recovery. Micro-model tests showed that emulsification and IFT reduction was the main EOR mechanism of the YZ biosurfactant in the oil wet model. In summary, these findings highlight the potential of Brevibacillus borstelensis YZ-2 and its metabolites for MEOR.

Study on the Effect of Threshold Pressure Gradient on Remaining Oil Distribution in Heavy Oil Reservoirs.

Due to the spatial network structure, heavy oil has a high threshold pressure gradient when it flows through porous media, and the threshold pressure gradient plays a crucial role in the distribution of remaining oil. In previous study, the common methods to measure the threshold pressure gradient include the microflow-established differential pressure (MFEDP) method, capillary equilibrium method, and the percolation curve fitting method. In this study, a sample from the SZ36-1 oilfield was analyzed for the basic physical properties based on the comparison of the previous measurement to study the influence of mobility on the threshold pressure gradient and then an independently developed numerical simulator was established to study the effect of the threshold pressure gradient on the remaining oil distribution considering the permeability range, crude oil viscosity, well network deployment, well spacing, and fluid recovery rate. The results show that the SZ36-1 oilfield fluid belongs to Bingham fluids with yield stress and the mobility having an exponent relation to the threshold pressure gradient based on the measurement of the MFEDP method. Considering the threshold pressure gradient of heavy oil, the uneven distribution of remaining oil is intensified and the remaining oil is enriched. This study provides a reference for efficient development of heavy oil reservoirs.

Polymer Flooding in Heterogeneous Heavy Oil Reservoirs: Experimental and Simulation Studies.

Polymer flooding (PF) in heterogeneous heavy oil reservoirs is not only closely related to polymer degradation, but also to non-Newtonian flow. In this paper, both experimental and simulation methods are combined to investigate this type of flooding. Through experiments, the degradation of polymer, rheological properties of fluids, and flow of fluids in porous media were determined. Based on the experimental results, a novel mathematical model was established, and a new PF simulator was designed, validated, and further applied to study the effects of polymer degradation, polymer solution shear thinning, and non-Newtonian flow on PF in heterogeneous heavy oil reservoirs. These experimental results demonstrated that the polymer first-order static degradation rate constant was lower than the polymer first-order dynamic degradation rate constant; the polymer solution and heavy oil were non-Newtonian fluids, with shear thinning and Bingham fluid properties, respectively; and the heavy oil threshold pressure gradient (TPG) in low-permeability porous media was higher than that in high-permeability porous media. All comparison results showed that the designed simulator was highly accurate and reliable, and could well describe both polymer degradation and non-Newtonian flow, with special emphasis on the distinction between polymer static and dynamic degradation and heavy oil TPG. Furthermore, the simulation results verified that polymer degradation, polymer solution shear thinning, and heavy oil TPG all had negative effects on the efficiency of PF in heterogeneous heavy oil reservoirs.

Tracking alterations of alkyl side chains of N1 species in heavy crude oil after anaerobic biodegradation with negative-ion electrospray ionization coupled with high-field Fourier transform ion cyclotron resonance mass spectrometry.

RATIONALE: Heteroatomic compounds are relatively abundant and believed to be bio-resistant in heavy crude oils. However, few studies have focused on the biodegradation of these heteroatomic compounds. METHODS: Heteroatoms, especially N1 species, in a blank crude oil and in three treated oils co-incubated with anaerobic sulfate-reducing bacteria, nitrate-reducing bacteria and fermentative consortia cultures were detected using negative-ion electrospray ionization coupled with high-field Fourier transform ion cyclotron resonance mass spectrometry. RESULTS: The relative abundance of N1 species in the three treated oils decreased, while the relative abundance of O2 species increased. Remarkably, the relative abundances of N1 species with low carbon number increased and those with higher carbon number decreased. CONCLUSIONS: These results revealed that the anaerobic biodegradations of heavy crude oil occurred. With direct evidences, the degradations of alkyl side chains of N1 species by the anaerobic microbes could be deduced.

Effect of Polymer Degradation on Polymer Flooding in Heterogeneous Reservoirs.

Polymer degradation is critical for polymer flooding because it can significantly influence the viscosity of a polymer solution, which is a dominant property for polymer enhanced oil recovery (EOR). In this work, physical experiments and numerical simulations were both used to study partially hydrolyzed polyacrylamide (HPAM) degradation and its effect on polymer flooding in heterogeneous reservoirs. First, physical experiments were conducted to determine basic physicochemical properties of the polymer, including viscosity and degradation. Notably, a novel polymer dynamic degradation experiment was recommended in the evaluation process. Then, a new mathematical model was proposed and an in-house three-dimensional (3D) two-phase polymer flooding simulator was designed to examine both polymer static and dynamic degradation. The designed simulator was validated by comparison with the simulation results obtained from commercial software and the results from the polymer flooding experiments. This simulator further investigated and validated polymer degradation and its effect. The results of the physical experiments showed that the viscosity of a polymer solution increases with an increase in polymer concentration, demonstrating their underlying power law relationship. Moreover, the viscosity of a polymer solution with the same polymer concentration decreases with an increase in the shear rate, demonstrating shear thinning. Furthermore, the viscosity of a polymer solution decreased with an increase in time due to polymer degradation, exhibiting an exponential relationship. The first-order dynamic degradation rate constant of 0.0022 day-1 was greater than the first-order static degradation rate constant of 0.0017 day-1. According to the simulation results for the designed simulator, a 7.7% decrease in oil recovery, after a cumulative injection volume of 1.67 pore volume (PV) was observed between the first-order dynamic degradation rate constants of 0 and 0.1 day-1, which indicates that polymer degradation has a detrimental effect on polymer flooding efficiency.

Effect of Non-Newtonian Flow on Polymer Flooding in Heavy Oil Reservoirs.

The flow of polymer solution and heavy oil in porous media is critical for polymer flooding in heavy oil reservoirs because it significantly determines the polymer enhanced oil recovery (EOR) and polymer flooding efficiency in heavy oil reservoirs. In this paper, physical experiments and numerical simulations were both applied to investigate the flow of partially hydrolyzed polyacrylamide (HPAM) solution and heavy oil, and their effects on polymer flooding in heavy oil reservoirs. First, physical experiments determined the rheology of the polymer solution and heavy oil and their flow in porous media. Then, a new mathematical model was proposed, and an in-house three-dimensional (3D) two-phase polymer flooding simulator was designed considering the non-Newtonian flow. The designed simulator was validated by comparing its results with those obtained from commercial software and typical polymer flooding experiments. The developed simulator was further applied to investigate the non-Newtonian flow in polymer flooding. The experimental results demonstrated that the flow behavior index of the polymer solution is 0.3655, showing a shear thinning; and heavy oil is a type of Bingham fluid that overcomes a threshold pressure gradient (TPG) to flow in porous media. Furthermore, the validation of the designed simulator was confirmed to possess high accuracy and reliability. According to its simulation results, the decreases of 1.66% and 2.49% in oil recovery are caused by the difference between 0.18 and 1 in the polymer solution flow behavior indexes of the pure polymer flooding (PPF) and typical polymer flooding (TPF), respectively. Moreover, for heavy oil, considering a TPG of 20 times greater than its original value, the oil recoveries of PPF and TPF are reduced by 0.01% and 5.77%, respectively. Furthermore, the combined effect of shear thinning and a threshold pressure gradient results in a greater decrease in oil recovery, with 1.74% and 8.35% for PPF and TPF, respectively. Thus, the non-Newtonian flow has a hugely adverse impact on the performance of polymer flooding in heavy oil reservoirs.

High quality genome sequence and description of Enterobacter mori strain 5-4, isolated from a mixture of formation water and crude-oil.

Enterobacter mori strain 5-4 is a Gram-negative, motile, rod shaped, and facultatively anaerobic bacterium, which was isolated from a mixture of formation water (also known as oil-reservior water) and crude-oil in Karamay oilfield, China. To date, there is only one E. mori genome has been sequenced and very little knowledge about the mechanism of E. mori adapted to the petroleum reservoir. Here, we report the second E. mori genome sequence and annotation, together with the description of features for this organism. The 4,621,281 bp assembly genome exhibits a G + C content of 56.24% and contains 4,317 protein-coding and 65 RNA genes, including 5 rRNA genes.

Permanent draft genome sequence of Bacillus flexus strain T6186-2, a multidrug-resistant bacterium isolated from a deep-subsurface oil reservoir.

Previous studies suggest that antibiotic resistance genes have an ancient origin, which is not always linked to the use of antibiotics but can be enhanced by human activities. Bacillus flexus strain T6186-2 was isolated from the formation water sample of a deep-subsurface oil reservoir. Interestingly, antimicrobial susceptibility testing showed that this strain is susceptible to kanamycin, however, resistant to ampicillin, erythromycin, gentamicin, vancomycin, fosfomycin, fosmidomycin, tetracycline and teicoplanin. To explore our knowledge about the origins of antibiotic resistance genes (ARGs) in the relatively pristine environment, we sequenced the genome of B. flexus strain T6186-2 as a permanent draft. It represents the evidence for the existence of a reservoir of ARGs in nature among microbial populations from deep-subsurface oil reservoirs.

Permanent draft genome sequence of Geobacillus thermocatenulatus strain GS-1.

Geobacillus thermocatenulatus strain GS-1 is a thermophilic bacillus having a growth optimum at 60°C, capable of degrading alkanes. It was isolated from the formation water of a high-temperature deep oil reservoir in Qinghai oilfield, China. Here, we report the draft genome sequence with an estimated assembly size of 3.5Mb. A total of 3371 protein-coding sequences, including monooxygenase, alcohol dehydrogenase, aldehyde dehydrogenase, fatty acid-CoA ligase, acyl-CoA dehydrogenase, enoyl-CoA hydrogenase, hydroxyacyl-CoA dehydrogenase and thiolase, were detected in the genome, which are involved in the alkane degradation pathway. Our results may provide insights into the genetic basis of the adaptation of this strain to high-temperature oilfield ecosystems.

Genome sequence of Brevibacillus agri strain 5-2, isolated from the formation water of petroleum reservoir.

Brevibacillus agri strain 5-2 was isolated from the formation water of a deep oil reservoir in Changqing Oilfield, China. This bacterium was found to have a capacity for degrading tetradecane, hexadecane and alkanesulfonate. To gain insights into its efficient metabolic pathway for degrading hydrocarbon and organosulfur compounds, here, we report the high quality draft genome of this strain. Two putative alkane 1-monooxygenases, one putative alkanesulfonate monooxygenase, one putative alkanesulfonate transporter, one putative sulfate permease and five putative sulfate transporters were identified in the draft genome. The genomic data of strain 5-2 may provide insights into the mechanism of microorganisms adapt to the petroleum reservoir after chemical flooding.