fractured well
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Pressure transient analysis for a vertically hydraulically fractured well is evaluated using two different equations, which cater for linear flow at the early stage and radial flow in the later stage. However, there are three different stages that take place for an analysis of pressure transient, namely linear, transition and pseudo-radial flow. The transition flow regime is usually studied by numerical, inclusive methods or approximated analytically, for which no specific equation has been built, using the linear and radial equations. Neither of the approaches are fully analytical. The numerical, inclusive approach results in separate calculations for the different flow regimes because the equation cannot cater for all of the regimes, while the analytical approach results in a difficult inversion process to compute well test-derived properties such as permeability. There are two types of flow patterns in the fracture, which are uniform and non-uniform, called infinite conductivity in a high conductivity fracture. The study was conducted by utilizing an analogous study of linear flow equations. Instead of using the conventional error function, the exponential integral with an infinite number of wells was used. The results obtained from the developed analytical solution matched the numerical results, which proved that the equation was representative of the case. In conclusion, the generated analytical equation can be directly used as a substitute for current methods of analyzing uniform flow in a hydraulically fractured well.

Abstract This paper reports the development and testing, of a Phosphate controlled dissolution glass composition used to strengthen the matrix of chalk whilst retaining the permeability of the rock, facilitating improved hydrocarbon recovery in unstable wells. Multiple versions of the glass solutions and different types of colloidal silica were extensively tested in the laboratory to determine injectability and reactivity with calcium carbonate rocks. The goal of the testing was to determine the best performing solution for use in a field trial in the Norwegian North Sea. The laboratory testing included filtration and core flood tests to determine the injectability of the solutions and post treatment permeability, and Brazilian strength tests to determine the tensile strength of the treated chalk cores. The filterability was tested through filter screen sizes ranging from 5 to 0.6 µm. Core flood testing was performed on 10 cm long chalk cores with 1.5 mD permeability. The glass solutions showed the best results in the filtration and core flood testing, achieving significantly greater invasion depth than any of the colloidal silica samples. The phosphate glass treated chalk cores maintained 70 to 100% of the original permeability while delivering a 3 to 5 fold tensile strength increase. The lab tests demonstrated the potential of a glass based treatment to strengthen chalk formations without impeding permeability.Based on the promising results from the lab tests, it was decided to trial the selected glass solution in a mature vertical proppant fractured well. The test confirmed that the glass solution could be pumped into the well, but the test failed pre-maturely after two months of varied production, and the trial will not be covered in this paper.However, due to the high value in being able to stabilize chalk in the field, the Operator is evaluating a new trial in a horizontal well, and learnings from the first trial will be used to inform further lab tests in the next phase. The glass solution used in this trial is being further developed to be used in other formation types, such as sand and non-calcium containing reservoirs.

Abstract The reliability of well-testing interpretation largely depends on the experience of reservoir engineers, which make the issue of non-unique solution serious and increase its application threshold. Virtually, deep learning assistive techniques are good strategies in well-testing interpretation. Although some work has been done based on automatic interpretation techniques, there is still a lack of an automatic interpretation model with wide applicability and fast interpretation on parameter evaluation of vertically fractured well. To improve this situation and make the well-testing interpretation easier to apply, this paper uses deep learning methods to build an automatic interpretation model of well-testing data for vertically fractured well. The model can automatically identify the corresponding parameters. The results in the validation set show that the median relative error of the curve parameter inversion is less than 10%. In addition, the accuracy of parameter prediction can be improved by increasing the weight of some important parameters in deep learning model training, such as permeability and fracture half-length. Finally, the automatic interpretation model is tested on a field case. The test results prove that the model has high accuracy and interpretation speed.

As exploration progresses, complex block formations and mid-deep formations have become the main target areas in Bohai oil fields. In this context, well leaks and well wall instability due to special lithology are becoming more and more likely to occur, and have become the most common complications affecting the safety of drilling operations and production timing in the Bohai Sea. Geological risk prediction can give engineering hints at the design stage, so that the engineering is in a position to prepare for the risks, but because the risk prediction given on conventional seismic profiles is relatively rough, the practical application deviates greatly and cannot be closely integrated with the actual operation. In this paper, we analyze the data of leaking wells in the Bohai exploration wells, summarize the leaking well tectonic background and stratigraphy, and divide the leak-prone tectonic zone. By extracting suitable seismic attributes such as variance and waveform, fine prediction of weak (fractured) well sections is realized, and a set of fine identification techniques is formed to "avoid", "prevent" and "plug" well leaks. "avoid", "prevent" and "plug" well leakage. This technology has been applied in several exploration wells in the Bohai Sea, and it has played a good effect and is of great significance to promote.

Hydraulic fracturing has been established as one of production enhancement methods in the petroleum industry. This method is proven to increase productivity and reserves in low permeability reservoirs, while in medium permeability, it accelerates production without affecting well reserves. However, production result looks scattered and appears to have no direct correlation to individual parameters. It also tend to have a decreasing trend, hence the success ratio needs to be increased. Hydraulic fracturing in the South Sumatra area has been implemented since 2002 and there is plenty of data that can be analyzed to resolve the relationship between actual production with reservoir parameters and fracturing treatment. Empirical correlation approach and machine learning (ML) methods are both used to evaluate this relationship. Concept of Darcy's equation is utilized as basis for the empirical correlation on the actual data. The ML method is then applied to provide better predictions both for production rate and water cut. This method has also been developed to solve data limitations so that the prediction method can be used for all wells. Empirical correlation can gives an R2 of 0.67, while ML can gives a better R2 that is close to 0.80. Furthermore, this prediction method can be used for well candidate selection means.

Abstract In the past decades, most oil explotation in the White Tiger oil field was produced from the basement reservoir. However, in recent years, these pay zones consist of basement reservoirs, Oligocene reservoirs, and Miocene reservoirs of which oil field s have been declined in oil production rate due to several issues such as complex fracture network, high heterogeneity formation, high water cut, and the reduction of reservoir pressure. The huge issues in the most production wells at basement reservoir were high water cut and it has been significantly increasing during oil production yearly. Therefore, the total amount of oil production in all pay zones sharply decreased with time. At present, the lower Miocene reservoir is one of the best tight oil reservoirs to produce oil extractrion. The lower Miocene reservoir has been faced some issues such as high heterogeneity, complex structure, catastrophic clay swelling, low connectivity among the fractures, low effective wellbore radius and the reservoir that is hig h temperature up to 120°C, the closure pressure up to 6680psi, reservoir pressure up to 4500 psi, reservoir depth up to 3000m. Another reason low conductivity consists of both low reservoir porosity ranging from 1% of the hard shale to 10% of the sandstone formation, and the low permeability raining from 1md to 10md. By considering the various recovery methods, the integrated hydraulic fracturing stimulation is the best tool to successfully stimulate this reservoir, which method allows an increase in oil production rate. In the post fractured well has been shown an increase in productivity over 3 folds in comparison with the base case with fracture half-length nearly 75m, and fracture conductivity about 5400md.ft, which production rate is higher than the production rate of the base case. In addition, the proppant mass is used of 133,067 lbs of which the first main stage is to pump sinter lite bauxite proppant type of 20/40 into the fractures and the next big stage is to pump sintered ball bauxite proppant size of 16/30 into the fractures, which not only isolate proppant flow back but also increase fracture conductivity at the near wellbore as wel as high productivity rate after fractured well. To improve proppant transport, fract uring fluid systems consist of Guar polymer concentration of 11.2 pptg with these additives to form a total leak-off coefficient of 0.00227 ft/min0.5.