A new well testing response from lateral cross flow within layers is described. The response occurs when there is extremely low effective vertical permeability in the system at the larger scale. Low vertical permeability actually accentuates the layering and reduces vertical cross flow whilst enhancing lateral cross flow from within-layer heterogeneities. The response is investigated using numerical simulation of flow in end-member models of complex and geologically realistic architecture in high net-to-gross fluvial systems. This ‘ramp’ response is shown to form one member of a family of well test pressure transient responses. The other members of the family include previously-described negative geoskin and geochoke. The use of well test data to characterize these particular types of layered fluvial reservoirs is an important step in the static-dynamic integration of geological and reservoir engineering models.
The process of reservoir history-matching is a costly task. Many available history-matching algorithms either fail to perform such a task or they require a large number of simulation runs. To overcome such struggles, we apply the Gaussian Process (GP) modeling technique to approximate the costly objective functions and to expedite finding the global optima. A GP model is a proxy, which is employed to model the input-output relationships by assuming a multi-Gaussian distribution on the output values. An infill criterion is used in conjunction with a GP model to help sequentially add the samples with potentially lower outputs. The IC fault model is used to compare the efficiency of GP-based optimization method with other typical optimization methods for minimizing the objective function. In this paper, we present the applicability of using a GP modeling approach for reservoir history-matching problems, which is exemplified by numerical analysis of production data from a horizontal multi-stage fractured tight gas condensate well. The results for the case that is studied here show a quick convergence to the lowest objective values in less than 100 simulations for this 20-dimensional problem. This amounts to an almost 10 times faster performance compared to the Differential Evolution (DE) algorithm that is also known to be a powerful optimization technique. The sensitivities are conducted to explain the performance of the GP-based optimization technique with various correlation functions
With the current focus on liquids-rich shale plays (LRS) in North America and the importance of gas condensate reservoirs globally, there is an increased need to develop reservoir engineering methods to analyze such reservoirs. Commercialization of LRS plays is now possible due to new technology, such as multi-fractured horizontal wells (MFHW). Efficient production from such reservoirs necessitates understanding of flow mechanisms, reservoir properties and the controlling rock and fluid parameters. Production-decline analysis is a robust technique for analysis of production data and obtaining estimates of recoverable reserves. Nevertheless, these techniques, developed for conventional reservoirs, are not appropriate for ultra-low permeability reservoirs. There are substantial differences in reservoir performance characteristics between conventional and ultra-low permeability reservoirs. LRS reservoirs produce much leaner wellstreams compared to conventional reservoirs due to very low permeabilities that result in very large drawdowns. Methods for analysis of two-phase flow in conventional reservoirs, with underlying simplifying assumptions, are no longer applicable.
This paper discusses production data analysis of constant flowing bottomhole pressure (FBHP) wells producing from LRS (gas condensate) reservoirs. A theoretical basis is developed for a gas condensate reservoir during the transient linear flow (drawdown) period. The governing flow equation is linearized using appropriately defined two-phase pseudopressure and pseudotime functions so that solutions valid for liquids can be applied. The derived backward model is employed to compute the linear flow parameter, xf√k.
Simulation results show that the liquid yield will be approximately constant for LRS wells during the transient linear flow, from the early days of initial testing, if flowing BHP is almost constant. An analytical formulation is used to prove this finding for 1D transient linear flow of LRS wells.
The proposed production data analysis (PDA) method is illustrated using simulated production data for different fluid models and relative permeability curves. Fine-grid compositional and black oil numerical models are used to this purpose.
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