Upstream Oil and Gas Technology最新文献

This paper is concerned with the application of optimal control theory to the problem of tracking deep oil and gas borehole trajectories. Based on the methods of differential geometry, the mathematical model of the trajectory curve with its curvature representing controlling variable is elaborated in the form of ordinary differential equations: The objective functional chosen as integral curvature, length or cost of the borehole are considered. The techniques for the optimization problem solving are developed with the use of the continuous version of the step-by-step anti-gradient projection on the hyper-planes of linearized constraints. At every step of the minimization procedure, the constraints spoilt by the linearization operations are restored through the use of the Newton method. Some examples are considered for a borehole with fixed and shifting boundary positions under conditions of minimizing its total curvature and length. It is shown that it is possible to improve the smoothness of the borehole trajectory using the outlined approach, and in so doing, reduce the friction and resistance forces impeding the drill string motion.

This study presents two independent methodologies for estimation of original gas in place (OGIP) by production dynamics diagnostic of gas-condensate reservoir with no-flow outer boundary based on black-oil concept. Classic Blasingame decline-type curves are also extended to apply in gas-condensate reservoir to calculate kh. Both numerically simulated case and field data are used to demonstrate the applicability and validity of proposed methodologies.

One method develops a novel analytical model to obtain average reservoir pressure, OGIP and Diatz shape factor at the same time by coupling flow equation of gas-condensate reservoir for boundary dominated flow (BDF) and general material balance equation (GMBE). The two-phase variable-rate flow equation at late time for BDF is clearly and concisely derived in this study in terms of defined two-phase pseodopressure and two-phase material balance pseudotime. In addition, another innovative, simple and effective method for estimation of OGIP is proposed in this study requiring input data of only cumulative production of well and reservoir fluid PVT characteristics of Constant Volume Depletion (CVD) experiment. The fundamental concept of this method suggests that transient cumulative production GOR is determined by only current gas recovery degree and fluid PVT characteristics of the reservoir. Due to the accurate, simple and relaxed data-requiring nature of this method, widespread use in field to estimate OGIP of gas-condensate reservoir is potentially encouraging. On the contrary, if OGIP is already known, an intermediate equation of the method can also be applied to check accuracy of CVD experiment results from laboratory.

The first methodology extends OGIP estimation to gas-condensate reservoir from Blasingame and Lee (1988)’s method for dry-gas reservoir. Often used two-phase z factor, which is inconvenient to evaluate and easy to yield error, for gas-condensate reservoir in material balance equation is avoided in this methodology by applying more analytical and accurate Walsh et al. (1994)’s GMBE instead. The second methodology, to the authors’ knowledge, is the first proposed allowing OGIP estimation of gas condensate reservoir without requiring bottom hole flowing pressure (BHFP), pressure tests and complex calculation.

To convert the hazardous oil-based mud waste into a resource, this study has addressed reclaimed nanoclays and its application as a filler material for reinforcing polyamide 6 polymer matrix into a novel polymer composite material. This work focuses on the synergistic effect of complex mixture of various clay minerals reclaimed from oil-based mud waste on different mechanical properties in polyamide-6 (PA6)/oil-based mud fillers (OBMFs) nanocomposites. PA6/OBMFs nanocomposites were manufactured through the melt compounding of OBMFs with PA6 in a twin-screw extruder followed by injection moulding.

The study shows significant improvement for mechanical properties. For instance, the tensile properties increased with the incremental loadings of OBMFs in PA6 matrix. The Young's moduli were increased by 42% and 35% in PA6 with 7.5 and 10 wt% OBMFs nanocomposites respectively whereas the tensile strengths were increased by 24% and 16% in PA6 with 7.5 and 10 wt% OBMFs nanocomposites respectively. The flexural strength increased by 26% with the addition of OBMFs from 0 to 10 wt% in PA6. The storage modulus of the nanocomposite containing 10 wt% OBMFs was 16% higher than the storage modulus of neat PA6 at 30 °C, whereas at 60 °C (glass transition temperature, T_g of neat PA6) the storage modulus of PA6 with 10 wt% OBMFs was 56% higher than that of neat PA6. The study shows that the oil-based mud waste can be appropriately management to develop a new raw materials resource for polymer technology.

The monitoring, prediction and control of microbiologically influenced corrosion (MIC) are common challenges in the oil industry. This paper aims to optimize monitoring of souring and corrosion threat in oil field water handling systems using latest developments in molecular microbiological methods. Microbial quantification was performed using quantitative polymerase chain reaction (qPCR) method. Microbial population structure fingerprinting was done using next generation sequencing (NGS). The findings were compared with the corrosion rates and most probable number (MPN) values obtained from conventional serial dilution methods. The results show that molecular microbiology methods provide faster and optimum corrosion mitigation strategies.

During the early phases of offshore oil field development, field planners must decide upon general design features such as the required number of wells and maximum oil processing capacity (field plateau rate), usually by performing sensitivity studies. These design choices are then locked in subsequent development stages and often prevent from achieving optimal field designs in later planning stages when more information is available and uncertainties are reduced.

In the present study, we propose using numerical optimization of net present value (NPV) to advice field planners when deciding on the appropriate number of wells, maximum oil processing capacity (plateau rate) in a Brazilian offshore oil field. Differential Evolution (DE) is employed for solving the optimization models. The uncertainties considered are well productivity and initial oil-in-place, handled by (1) using the mean of the distributions and (2) Monte Carlo simulation. A multi-objective optimization was also formulated and solved including ultimate recovery factor in addition to net present value.

The proposed method successfully computes probability distributions of optimal number of wells, plateau rate and NPV. If one wishes to compute the mean of such distributions only, for most cases it is adequate to run an optimization using the mean of the input values instead of performing Monte Carlo sampling. The multi-objective optimization allows to find field designs with high ultimate recovery factor and high NPV. In this case, the value of NPV is similar to the optimum NPV value when optimizing NPV only. The methods described could provide decision support to field planners in early stages of field development.

Several empirical correlations for prediction of wellhead gas flow rate have been presented in the literature. In this study, subcritical wellhead choke flow data of gas condensate wells that cover a wide range of flow rates (5.4–113 MMSCF/D) and choke sizes (32–192 64th in) were used to develop an intelligent prediction method. Subcritical two-phase flow wellhead choke data from 193 tests of gas condensate wells in 10 fields have been used. Measured pressure drop across the choke, gas to liquid ratio (GLR) and choke size were the input parameters. PSO-LSSVM method was applied to field-measured test data and optimized model parameters were obtained for prediction of gas flow rate as objective function. In addition, the results were compared with recently published empirical correlations developed for subcritical flow. Accuracy of the proposed model were evaluated with error parameters; AARD (average absolute relative deviation), RSME (relative square mean error), and R-squared. Results show the superiority of the proposed model with high accuracy. Observed data and model prediction matched very well with R² of 0.9996 and RMSE of 1.46. In addition, five test data that have not been used in the process of model development (training and testing) were used to assess the generality of the proposed mode. Very good agreement between model prediction and observed gas flow rate data was obtained and can be used for estimation of gas flow rate of subcritical chokes with high confidence.

The inclusion of nanomaterials in laboratory prepared mud has recently become a common approach to determine the mud properties. As the properties of laboratory prepared mud change while circulating through the wellbore, it is essential to investigate the effect of nanoparticles on the properties of field used mud. Field used mud is taken from the ongoing drilling of a non-reservoir section (1200 to 2585 m) of an exploratory well; located in Srikail Gas field, Bangladesh. In this study, iron (III) oxide nanoparticles are introduced both in laboratory prepared and field used low solid non-dispersed water base mud at different concentrations of 0.1, 0.5, 1.0, and 3.0 wt%. Field used mud shows higher apparent viscosity, yield stress (1.61%), 10 s gel strength (100%) and 10 min gel strength (133.33%) compared to laboratory prepared mud at a nanoparticles concentration of 0.1 wt%. Moreover, the field used nano-base mud demonstrates superior filtration properties at lower concentrations compared to laboratory prepared nano-base mud. The addition of 0.1 wt% nanoparticles in field used mud reduces the filtrate volume and cake thickness by 40% and 47%, respectively. In most cases, the rheological and filtration properties of field used mud are found to be better than those of the laboratory prepared mud. The results also show that a low concentration of iron (III) oxide nanoparticles can be functioned as an additive in the mud system to get the better filtration and rheological properties.

This study presents a robust artificial neural network technique to estimate the fracture network properties including fracture density and fractal dimension to create the reservoir subsurface fracture map. Overcoming the limitations of the used data in characterizing the fracture properties is deeply investigated in this study by employing the neural network technique to establish a relationship between available data by developing a new correlation using conventional well logs and borehole images. Subsequently characterize fracture properties in terms of fracture density and fractal dimension. The neural network system in this study is developed based on FORTRAN language to establish in house code with the back-propagation algorithm as a learning procedure. The sigmoid function is used as well for output prediction. Two new correlations are generated, one for fractal dimension and other one for fracture density as function of conventional well logs. The developed correlations are used to generate a continuous 3D subsurface fracture map for the studied reservoir. The data are collected from five wells drilled in the reservoir include conventional well logs and Full bore micro-resistivity image data. The used data are distributed 80% for the training and 20% for the testing only from 4 wells. The results show that, the developed correlations able to predict the fracture properties precisely with mean square error = 0.05 and R square = 0.997 for the training process and with R square = 0.97 for testing. A validation is performed using a data from well#5 which are not used in the training process. The results of validation show that fracture properties are predicted with R square = 0.99. The subsurface fracture map for the studied reservoir is successfully generated using the obtained 3D fractal dimension and fracture density. In addition, the created subsurface fracture map is validated by using the available reservoir production data.

In recent years, Computational Fluid Dynamics (CFD) modelling methods have been applied to study the behavior of a single elongated bubble in stagnant and flowing liquid. To date, only very few studies have been performed for slightly upwardly inclined pipes. This work presents mostly 2D numerical simulations based on the Volume of Fluid approach, dealing with the characteristics of a single elongated bubble injected into a liquid in a slightly upwardly inclined pipe. CFD-based results were compared with experimental results. In general, except the numerical bubble length, drift velocity, bubble fraction and bubble shape, agreed fairly with the experimental outcomes.

Shale swelling inhibition property in water-based drilling fluid (WBDF) is an important issue in drilling fluid engineering. Against the importance of chemical compounds used to give this property to the drilling fluid, sequence of adding those additives is also much of concern. In the presented study, we propose an optimized sequence of additives in the formulation of a standard WBDF. In the formulation, potassium chloride (KCl), partially hydrolyzed polyacrylamide polymer (PHPA), and polyglycol are used as major shale inhibitors. Therefor, 23 drilling fluid samples with variation in sequences of adding additives were experimented. Then 16 different WBDF samples were produced through changing the position of KCl, PHPA, bentonite and polyglycol and more 6 drilling fluids were prepared by simultaneous change in the position of PHPA, bentonite and KCl. Also, one oil-based drilling fluid (OBDF) was also produced and experimented against shale inhibition for performance comparison. Analyzing of swelling curves of all these drilling fluids revealed three different behaviors of them in shale inhibition. Then after, the optimized sequence of adding the shale inhibitors was defined according to the best observed performance of all experimented fluids. It should be noted that the presented study only focuses on the inhibition of swelling of cuttings and not on the dispersion of cuttings.