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The objective of this study is to analyze in detail a process for designing by means of numerical simulation a field test of gas production from hydrate deposits, and to discuss modeling results associated with several such planned tests. The paper discusses comprehensively the data required for a reliable estimate of gas production, and provides insights into production conditions and test well operating parameters that can adversely affect a planned test. The design process begins with the development of a reliable geologic model. It is followed by an analysis of the system stratigraphy, the identification of the hydrate-bearing zones and the associated interlayers, the definition of the initial conditions (pressure, temperature, phase distributions, and geomechanical stresses), the identification of all key media properties (flow, thermal, geomechanical), and the definition of success criteria for hydrate production tests.
The geologic model is of paramount importance because it can define the system boundaries. We explore the relative importance of lateral vs. top and bottom flow boundaries within the context of the limited time frame of a field test. Initial pressures P in hydrate accumulations are relatively predictable as they are almost invariably hydrostatic. The initial temperature T distribution is important because T is the dominant parameter controlling the hydrate behavior. Knowledge of the P and T distributions are important in determining true time-invariant P- and T-boundaries. Other important initial conditions are (a) the spatial distribution of the possible phases and (b) the geomechanical stresses in the system and its surroundings. We discuss possible sources of the necessary data through analogs even when direct measurements are unavailable. We investigate the effect of heterogeneity in various parameters, and in the choice of the coordinate system. We explore the impact of spatial discretization, an important subject that has yet to be fully investigated. Finally, we provide modeling results covering a wide range of designs for production tests in oceanic and permafrost-associated hydrate deposits that describe fluid production and the flow and geomechanical system response, as well as implications for the well design and construction.
To the authors' knowledge, this is the first paper discussing in detail the recommended process for the design of field tests of gas production from hydrates, and of the key issues that can affect not only production but also the flow and geomechanical behavior of the system during the test and the definition of the well construction requirements.
The world’s first offshore gas production test from methane hydrate deposits was conducted in March 2013, at the test site located on the margin of Daini Atsumi Knoll, off the coasts of Atsumi and Shima peninsulas, in the easten Nankai Trough, of Japan. Approximately 120,000 cubic meters of methane gas was produced in 6 days using the depressurization technique.
The test was a significant advance in Japan’s national program to construct the technical base for future commertial methane hydrate resource development. A series of researches for more than 10 years, including two times of onshore production tests in Mallik field and explorations in eastern Nankai Trough, were required to reach the test.
This report reviews Japan’s research history for methane hydrates.
Saurbayev, Ilyas (North Caspian Operating Company, now with Shell Kazakhstan) | Reedy, John (North Caspian Operating Company) | Bukharbayeva, Aigerim (North Caspian Operating Company) | Hatiboglu, Can (North Caspian Operating Company) | Massingill, Amber (North Caspian Operating Company)
The PDF file of this paper is in Russian.
This paper presents the use and value of information obtained from interference testing performed during the early production of Kashagan field. Numerous field examples of the interference and pulse tests are presented along with their implications for improving reservoir characterization and modeling. Design aspects of the conducted tests and an approach to address uncertainties in the pressure data are also described.
A significant amount of important interference data was captured during the start-up and subsequent ramp- up of Kashagan field. This included local well to well interference and pulse testing as well as an extended test that covered a larger area of the field. However, operational activities at observer wells complicated the available data and necessitated application of a pressure correction methodology. This methodology had to account for the inherent uncertainty in the interpretation of the data. Moreover, to increase our confidence in the interpretation, a dedicated pulse test was performed in the specific part of the field. Finally, responses from all observation wells were integrated and analyzed to capture big picture learnings from the early interference testing program.
When results of the interpreted interference response from all observers were combined, several groupings of wells became apparent. This helped to understand the degree of connectivity in various areas of the field. For dynamic model calibration, it was preferable to have a range of interference responses for each well to reflect uncertainty in the data. Therefore, so called "early" and "late" response curves were developed for each well. Overall, the collected and analyzed interference data was very useful in reducing uncertainty during this early period and will be used to optimize reservoir management decisions and future phases of the field development.
Results presented in this paper can be used by practicing engineers as another great example for advocating the use of permanent downhole gauges (PDHGs) and importance of proper planning and execution for the interference and pulse tests.
Abstract Isochronal testing is commonly used to evaluate the performance of gas wells. This paper proposes a new technique to estimate the value of turbulence coefficient based on isochronal tests. The proposed method is easy to apply and evaluate. Further, the method also provides a value of bg under stabilized conditions which can be used to predict the performance of gas wells under stabilized conditions. The proposed method is validated using field data under a variety of operating conditions. The values of turbulence coefficient based on the field data can differ significantly compared to the literature correlations. This further shows the importance of obtaining appropriate reservoir parameters based on the field rather than the lab data. Introduction The use of isochronal or modified isochronal testing is well established in the gas industry. These tests are common for gas wells which take a long time to reach a stabilized rate. A common example would be a low permeability, fractured reservoir. Instead of testing these wells till a stabilized rate is reached, the wells are tested for a fixed period of time and the bottom hole pressure is measured. For isochronal testing, the well is then shut in till it reaches a stabilized pressure and the procedure is repeated for different rate. For modified isochronal testing, the well is shut in for a fixed period of time, and the shut in pressure is measured at the end of that period. The procedure is then repeated at other rates. By repeating this procedure for different time intervals, we can gather information about rate versus pressure drop in the formation for these time intervals. Ultimately, using this information, our goal is to establish an appropriate rate versus pressure drop relationship under stabilized conditions. Two procedures are commonly used to establish the equation for rate versus pressure drop. An empirical method states that, (1) where qg is the gas rate, C and n are constants and p and pwf are average pressure and bottom hole pressure respectively. We can write a simpler equation in terms of pseudo-real pressures as, (2) where m(p) and m(pwf) are pseudo-real average pressure and pseudo-real bottom hole pressure respectively. Under transient conditions, the value of C is not constant. Instead, we can write Eq. 2 as, (3) where c(t) represents a term which is a function of isochronal interval t. In literature, methods are proposed to estimate the value of C corresponding to stabilized rate based on the transient state information −C(t). See e.g., Hinchman et al. In that paper, Hinchman et al. propose that be plotted as a function of log t, and the line be extrapolated till t is equal to the time it takes to reach stabilized state period. P. 223^
The PDF file of this paper is in Russian.
Matured oil field development poses different set of problems to be solved. As the geological structure is understood by this time, the most important tasks for reservoir surveillance becomes localization of residual reserves and the identification of promising zones for the production enhancement. Considering that the effect of potential geological and technical measures in the matured oilfield will not be that significant, the monitoring methods should be cost effective and at the same time deliver sufficient information. In our case, the main surveillance techniques were measurements of reservoir pressure, joint measurements of bottomhole pressure and well production rate, and targeted well tests. In addition, production logging was widely used to build the inflow and injection profile, identify sources of watering, and commingled production control. Authors implemented technology to assess the current skin factors without stopping such wells for special tests, only on the basis of the results of joint measurements of bottomhole pressure and well production.
The main low-cost method to remove the colmatation of the bottomhole zone was re-perforation, significantly increasing the flow rate of oil wells. In general, a comprehensive production analysis was carried out, including recovery evaluation by the zones of the reservoir and an areal analysis based on facies heterogeneity information. It was possible to achieve stabilization and even an increase in oil production after the suggested well intervention program was implemented in the field.