TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractThe use of permanent sensors provides a continuous source of downhole pressure measurement throughout the life of the well. Moreover, multiphase flowmeters provide simultaneous flow rate measurements. The significant amount of data produced by these sensors has added a new dimension to traditional well test data interpretation techniques. This new dimension is life -of-well time. During the life of the well, permanent-gauge data and flow rate measurements are affected by several dynamic factors including changes in reservoir pressure, skin, permeability-thickness ( kh), a nd reservoir drive mechanism. A major challenge facing the industry today is how to diagnose and respond to the effect of each of these factors. In other words, it is important to know whether a change in measured downhole pressure or flow rate is caused b y depletion, changes in skin, kh, or drive mechanism.This study investigates the effects of the above-mentioned factors in two fields in the Gulf of Mexico area. In addition, experience and lessons learned from numerous wells and fields equipped with permanent sensors have been used to develop a diagnostic method. This method uses key reservoir and well performance indicators to derive techniques to distinguish between the effects of depletion, skin, kh and drive mechanism. Best practices in the collection of flow rate and pressure data with suggestions for near-future improvements are included.

A systematic approach is presented for generating transient inflow performance relationship curves for finite conductivity vertically fractured wells. A semi-analytical model was developed to simulate dimensionless wellbore pressure drop and dimensionless pressure loss through the fracture vs. dimensionless time at constant-rate of production for wells intercepted by a finite-conductivity vertical fracture. Flowing bottom hole pressure can be predicted at any time period using these dimensionless variables. System average pressure at any stage of production can be obtained through material balance calculations. A straight line reference curve was observed at all times provided that the real gas pseudo-pressure function is used to plot m(pwf(t))/m(p¯R(t)) vs. qg(t)/qgmax (t). The advantage of normalizing the dimensionless variable in termas of pseudo-pressure function is that only one straight line relationship is obtained throughout the entire production life of the reservoir. This provides a more simple means for performance prediction purposes. The major contribution of this paper is the provision of a valuable tocl to study the sensitivity of fracture design parameters on ultimate well performance. The economic benefits of this approach can be substantial.

A completely new approach is presented to show the effect of completion parameters on high volume gas wells typical of the Gulf Coast. The solution can be summarized in graphical form and it will consider the following sections of the total producing system: 1) flow in the porous media, 2) effect of completion, and 3) flow conduit performance. The result is that the controlling parameter in the total production system can be determined. Many wells are capable of producing very high rates but are restricted due to very restricted gravel pack parameters, while wells with very efficient gravel pack completions are tubing-dominated. The procedure presented approaches the completion sensitivity analysis from a complete production system concept.

Nodal analysis is the standard technique used to evaluate the performance of integrated production systems. Two curves represent the capacities of the inflow and of the outflow, and the intersection of the two curves gives the solution operating point. Limitations of traditional nodal analysis include:• Results are offered only at a snapshot, not as a function of time.• Inflow-performance-relationship (IPR) models are limited, with none available for shale gas wells. • Analysis is performed on a well-by-well basis, with no account of multiwell interference. We propose a new nodal-analysis method that enables the study of transient production systems, such as unconventional reservoirs, with IPR models generated from a high-speed semianalytical reservoir simulator and outflow curves generated from a steady-state pipeline simulator. The use of analytical reservoir simulation allows accurate, reliable modeling of the real inflow system. The new approach studies the time-lapse behavior of the system, with consideration of production history and neighboringwell interference.This new method enables the study of transient deliverability at the wellhead, where the measurement is usually available, and shows the time-lapse relationship between wellhead pressure and production rate. We provide examples of wellhead deliverability and choke management and explain advantages of the method with case studies involving tight and shale wells. The method is also applied to design and optimize artificial lift in unconventional wells and to study the method's validity over time. In addition, we discuss an example of operational well dynamics with timelapse nodal analysis.Furthermore, this new method generates discussion about some concepts that are often taken for granted-What should be the definition of IPR in a transient production system? On the IPR curve, is the zero-rate-pressure the reservoir pressure? Can IPR curves at two different timesteps cross each other? Finding the answers to these questions will help us better understand production systems.The commonly used productivity-index (PI) method is reviewed and compared with the new method. Results show that one should not use the PI method when well operational conditions change.

A life-of-well comprehensive methodology for production optimization is demonstrated through two Gulf of Mexico stimulation treatments in formations requiring sand control. The approach considers the full well history in the process of well evaluation and candidate selection. The treatments were designed for remediation of damage caused by a time-dependent disruption of formation sand and/or sand-control mechanism, including fines migration, proppant instability, and scaling. Traditionally, data from permanent bottomhole gauges have been used as a valuable tool for well and reservoir management. As demonstrated in this paper, the data can be crucial to the assessment of the evolution of time-dependent skin. The practical result of well or reservoir surveillance and diagnosis from permanent gauge or traditional production data is shown to produce better decisions on stimulation and production management, while maintaining life-long well integrity. Introduction Completion optimization for sand control has been discussed in the literature by several authors.1,2 This paper deals with the identification and the remedial actions to reduce or remove completion damage associated with sand control for wells with and without permanent downhole pressure gauges (PDGs). With the balance required between the value of imformation and the overall economics of a development and exploitation project, it becomes extremely important to capture all events during the life of a well and to utilize all information to the fullest extent. The use of high-frequency data or continuous information has a great impact in the expansion of the traditional time scale, from the usual snapshot approach to a continuous evaluation and remedial action process. This process can lead to real-time production managemement and decision making. The integration of historical well information from different sources and continuous or high-frequency data, and their availability for practical use through proper evaluation tools, remains a challenge. However, the lessons learned are quickly developing a knowledge base that can greatly impact well and reservoir management in the future. Life-of-Well Approach Several factors play significant roles when dealing with completion decisions, especially in the offshore and deepwater environments. The feasibility for any development project rests not only on available reserves but also on the longevity and integrity of well completions. Critical early time and baseline well fingerprinting information is sometimes not available, or not recorded, which can significantly impact the decision-making process on all downstream operations. This situation is equally applicable to single- and multiwell cases. Completions requiring sand control are especially prone to time-dependent degradation due to the evolving formation and proppant mechanical conditions, which at the end impairs hydrocarbon production through the gravel pack and/or frac-pack elements. It is extremely important to be able to forecast realistic dynamic operating well conditions when planning a sand-control completion. Planning enables the selection of the most appropriate completion method, including the corresponding hardware configuration and job execution program to achieve the expected results. Fig. 1 presents the life-of-well approach for completion and production optimization. This continuous, perennial process is initiated at the early exploratory and development stages and continues until depletion and abandonment. Below is a brief description of the basic elements of this approach. WCP Forecast The life-of-well process begins with the well completion productivity (WCP) prediction that uses all reservoir static and dynamic information. The data are fed into the reservoir module of the predictive model, which will also include information about heterogeneity, lateral extent, and expected drive mechanism. In unconsolidated formations and/or those with stress-dependent porosity and permeability, a sand prediction model and a geomechanical model may be needed on a sandface or regional basis.