This paper presents a method to eliminate production loss due to liquid-loading in tight gas wells. Cyclic shut-in control is a simple production strategy that particularly benefits lower-permeability stimulated wells, including but not limited to shale gas wells. Comparison is made between a gas well producing (1) in a "ideal" situation where 100% of liquids entering from the reservoir or condensing in the tubing are continuously removed (without shut-ins), (2) in a meta-stable liquid-loading condition with low gas rate, typical of most wells today, and (3) by the proposed strategy of cyclic shut-in control. We show that cyclic shutin control of stimulated low-permeability vertical wells to ultra-low-permeability horizontal multi-fraced wells can produce without ever experiencing liquid loading, and with little-to-no delay of ultimate recovery. Cyclic shut-in control can be applied to all stimulated, lower-permeability gas wells, from the onset of gas rates that result in liquid-loading. The strategy can also be used for wells which already have experienced a period of liquid-loading, but the expected performance improvement may be less because of near-well formation damage caused by historic liquid-loading – e.g. fresh-water backflow and liquid-bank accumulation. In historically liquid-loading wells, an initial period of liquid removal and/or light stimulation may be needed prior to initiating cyclic shut-in control. We show that the shut-in period should optimally be as short as operationally possible. Cyclic shut-in control is shown to work equally well for layered no-crossflow systems with significant differential depletion at the onset of liquid loading. Minimizing rate and recovery loss of liquid-loading gas wells is of international interest. We believe that cyclic shut-in control will become an industry standard practice for shale gas wells, and should lead to a significant ultimate increase in worldwide gas reserves. The method is extremely simple and requires only a rate-controlled wellhead shut-in device.

A benchmark for computational integration of petroleum operations has been constructed. The benchmark consists of two gascondensate reservoirs producing to a common process facility. A fraction of the processed gas is distributed between the two reservoirs for gas injection. Total project economics are calculated from the produced streams and process related costs. This benchmark may be used to compare different computational integration frameworks, and optimization strategies.The methods of model integration and optimization discussed in this paper are applicable to complex petroleum operations where it is difficult to quantify cause-and-effect without comprehensive model-based integration. A framework for integration of models describing petroleum operations has been developed. An example test problem is described and studied in detail. Substantial gains in full-field development may be achieved by optimizing over the entire production system.All models and data in the benchmark problem are made available so that different software platforms can study the effects of alternative integration methods and optimization solver strategy. The project itself can, and probably should, be extended by others to add more complexity (realism) to the reservoir, process, and economics modeling.

This paper presents a backpressure equation (BPE) for wells producing from layered gas reservoirs with or without communication. The proposed BPE handles backflow between the layers through the wellbore for non-communicating layered systems, and accurately describes performance of wells experiencing differential depletion.The proposed multi-layer BPE has the same form as the familiar backpressure equation for single-layer gas reservoirs, where the correct averages are defined for reservoir pressure and backpressure constants.The BPE is validated against numerical simulation models, as well as field data which include decades of historical production performance and annual shut-in pressures. All numerical models and field data used to validate the BPE are publicly available. This paper gives guidelines on welltest design to quantify reservoir parameters in layered systems, based on systematic studies with numerical simulation models. BackgroundLayered reservoirs without communication, also referred to as layered no-crossflow reservoirs, consist of separate layers without communication within the reservoir; layers only communicate through the wellbore.One of the first attempts to study the transient performance of layered reservoirs was Lefkovits et al. (1961). They show individual layer gas rates as a function of each layer kh product, but do not consider production performance solutions for boundary-dominated (pseudosteady state, PSS) conditions. Fetkovich et al. (1990) studied and identified all key performance characteristics of layered no-crossflow systems producing under boundary-dominated conditions. One of their many important observations is Curve 6 in their Fig. 12, showing that the backpressure relation for a differentially depleting system is, in fact, a straight line with exponent n~1. We show, in this paper, that this is an expected and general observation for any layered system, and that the layered no-crossflow backpressure equation is the same as for a single-layer system with equal total kh, but using the layer PI-averaged shut-in pressure.El-Banbi and Wattenbarger (1996) developed a model to match production data from a layered no-crossflow system during boundary-dominated conditions, using individual-layer coupling of material balance and PSS rate equations. This model is used to estimate individual layer properties, for the assumption of constant bottomhole flowing pressure. Another attempt to estimate layer properties and gas in place for layered no-crossflow reservoirs was Kuppe et al. (2000). This work allows changes in bottomhole flowing pressure, but does not handle extended shut-ins resulting in backflow through the wellbore. This paper will primarily consider layered no-crossflow reservoirs, but some results are shown to be applicable to reservoirs with partially-or fully-communicating layers. The backpressure equation presented is valid for all layered reservoirs, but the coupled material balance approach is only valid for non-communicating layer systems.

Summary A benchmark for computational integration of petroleum operations has been constructed. The benchmark consists of two gas/ condensate reservoirs producing to a common process facility. A fraction of the processed gas is distributed between the two reservoirs for gas injection. Total project economics is calculated from the produced streams and process-related costs. This benchmark may be used to compare different computational integration frameworks and optimization strategies. Even though this benchmark aims to integrate all parts of a petroleum operation, from upstream to downstream, certain simplifications are made. For example, pipe flow from reservoir to process facility is not included in the integrated model. The methods of model integration and optimization discussed in this paper are applicable to complex petroleum operations where it is difficult to quantify cause and effect without comprehensive model-based integration. A framework for integration of models describing petroleum operations has been developed. An example test problem is described and studied in detail. Substantial gains in full-field development may be achieved by optimizing over the entire production system. All models and data in the benchmark problem are made available so that different software platforms can study the effects of alternative integration methods and optimization solver strategy. The project itself can, and probably should, be extended by others to add more complexity (realism) to the reservoir, process, and economics modeling.

This paper presents an integrated modeling approach for history matching and economic optimization of wells producing from liquid-rich shale reservoirs (LRSR). History matching uses daily pressures and gas-oil-water production data to estimate average parameters in a 2D/3D finite-difference (FD) horizontal multi-fractured well model: rock permeability, fracture halflength, relative permeabilities, and in-situ fluid (solution gas-oil ratio). Economic-based well design uses the same FD model to maximize net present value (NPV) by finding optimal well completion parameters: number of fractures, and fracture size. Revenue optimization (short-term and long-term) is performed with the same FD well model by finding the drawdown that maximizes revenue. For undersaturated gas condensate LRSR wells, optimal drawdown is often equal to or somewhat below the reservoir dewpoint pressure. We study optimal drawdown control for new wells that are optimized from start of production, and for wells that are optimized only after some initial period of sub-optimal drawdown control. We also compare short-term versus long-term economic optimization strategies.We provide examples that clearly show the potential for improved economic development of LRSR using optimized well design and drawdown control, for new and existing wells. Our study shows a significant economic upside to proper selection of completion design, and for undersaturated gas condensate wells, optimal drawdown has significant potential to increase daily revenues.