fax 01-972-952-9435. AbstractThis paper analyzes the effect of stress on the rock properties fracture and matrix compressibilities, fracture and matrix porosities, and permeability in naturally fractured reservoirs (NFRs).In NFRs, fluids are stored inside the matrix pore space and inside the fractures of the rock. The reservoir characterization parameter indicating the volumetric fraction of fluids deposited inside the fractures is the storage capacity ratio, which is function of the fracture and matrix porosity, and fracture and matrix total compressibilities. Due to the difficulty to obtain these values, in reservoir engineering computations such as pressure transient analysis and reservoir simulation, among others, it is generally assumed that the matrix and the fracture total compressibilities are equal. This induces a big uncertainty in the estimation of the storage capacity ratio and leads to a wrong estimation of the volume of fluids inside the fractured rock.Changes in pore pressure due to production or injection of fluids affect the effective reservoir in-situ stress. The mechanical behavior of the fractured rock and its effects on the rock properties permeability, porosity and compressibility in the matrix and fracture frames are analyzed using the elastic properties bulk modulus and normal compliance of the fracture. These properties can be obtained from petrophysical core analysis or multi-component seismic interpretation, and linked to pressure transient analysis through the storage capacity ratio equation. A step-by-step procedure of the analysis is presented and illustrated with an example for quantifying the effects of changes in effective stress on the fracture and matrix compressibilities.
This paper analyzes the effect of stress on the rock properties fracture and matrix compressibilities, fracture and matrix porosities, and permeability in naturally fractured reservoirs (NFRs). In NFRs, fluids are stored inside the matrix pore space and inside the fractures of the rock. The reservoir characterization parameter indicating the volumetric fraction of fluids deposited inside the fractures is the storage capacity ratio, which is function of the fracture and matrix porosity, and fracture and matrix total compressibilities. Due to the difficulty to obtain these values, in reservoir engineering computations such as pressure transient analysis and reservoir simulation, among others, it is generally assumed that the matrix and the fracture total compressibilities are equal. This induces a big uncertainty in the estimation of the storage capacity ratio and leads to a wrong estimation of the volume of fluids inside the fractured rock. Changes in pore pressure due to production or injection of fluids affect the effective reservoir in-situ stress. The mechanical behavior of the fractured rock and its effects on the rock properties permeability, porosity and compressibility in the matrix and fracture frames are analyzed using the elastic properties bulk modulus and normal compliance of the fracture. These properties can be obtained from petrophysical core analysis or multi-component seismic interpretation, and linked to pressure transient analysis through the storage capacity ratio equation. A step-by-step procedure of the analysis is presented and illustrated with an example for quantifying the effects of changes in effective stress on the fracture and matrix compressibilities. Introduction Well test analysis has been one of the most basic tools to characterize and quantify properties such as permeability, storage capacity ratio and the interporosity flow parameter in naturally fractured reservoirs. This reservoir characterization study integrates several geosciences such as: Petrophysics, Rock Mechanics, Seismic, Geophysics, Reservoir Engineering, and Production Engineering to investigate and quantify the effect of stress on several rock properties: permeability, compressibility, and porosity of naturally fractured reservoirs. Dual Porosity Models These models are used to simulate reservoir systems composed of two different types of porosity, matrix and fracture that coexist in a rock volume. It is usually assumed that the matrix consists of a set of porous rock systems that are not connected to each other, have a low transmissibility and have a high storage capacity. Furthermore, it is also assumed that the fracture system has low storage capacity, high transmissibility and it interconnects the porous media. Most dual porosity models assume that the matrix provides the fluids to the fractures, and the fractures transport the fluids to the well. As shown in Figure 1, different idealizations of the matrix/fracture geometry have been proposed such as the sugar cube model by Warren and Root 1, parallel horizontal fractures by Kazemi 2 and match-stick column models by Reiss 3. The multi-porosity model proposed by Abdassh and Ershaghi 4 is a variation of the dual porosity model, which assumes a fracture set that interacts with two groups of matrix blocks with different porosities and permeabilities.
In naturally fractured reservoirs (NFRs), current analyses for quantifying reserves based on the material balance equation (MBE) assume that fractured reservoirs behave similar to homogeneous reservoirs, which implies that the fracture and matrix pore volume compressibilities are equal. There is considerable evidence that such assumption is not always valid leading to wrong estimation of reserves. In order to overcome this deficiency a complete treatment of the material balance formulation for naturally fractured reservoirs is presented. The proposed general MBE takes into account the fact that fracture and matrix pore volume compressibilities are different. This equation is used to investigate the impact of pressure depletion on the estimation of oil in place and recovery factors. As results of this study, new equations to compute hydrocarbons originally in place in NFRs are developed for undersaturated and saturated reservoirs. New plotting schemes for the MBE involving the storage capacity ratio at initial reservoir conditions of fracture and matrix pore volume compressibilities are proposed. The capacity ratio is computed from pressure transient test performed during the early stages of production. These new plotting schemes requires only one regression parameter, the slope of a straight line passing through the origin on a Cartesian plot, which reduces the uncertainty that traditionally two regression parameters (intercept and slope) introduces; as consequence, better estimation of oil in place with fewer historical production data can be obtained. This new method is illustrated by several field examples. It is concluded that (a) the proposed material balance formulation gives better estimation of oil in place than the traditional MBE computations; (b) the split of hydrocarbons originally in place between fracture and matrix frames depends upon the storage capacity ratio at initial reservoir conditions and; (c) the impact of pressure depletion on the estimation of reserves and recovery factors in naturally fractured reservoirs is significant. Introduction This paper presents methods to quantify hydrocarbons in place and recovery factors taking into account the differences between fracture and matrix pore volume compressibilities, and their changes caused by pressure depletion for undersaturated and saturated naturally fractured reservoirs. Such methods are based upon the integration between pressure transient analysis and the material balance equation. For undersaturated reservoirs, the assumption that matrix and fracture pore volume compressibilities are equal leads to underestimations of the fractional recovery. For saturated reservoirs only negligible differences in estimation of reserves and recovery factors have been observed. The General Material Balance Equation for Naturally Fractured Reservoirs The link between the elastic behavior of the rock and the recovery predictions in the material balance modeling resides in the effective compressibility term and the storage capacity ratio. Therefore, to model the effect of changes in stress due to changes in pore pressure in the fracture system, the general volumetric material balance equation must be modified using the correct effective compressibilities of the fracture rock. The general MBE, initially presented for homogeneous reservoirs by Schilthuis 1, has been improved by Chacon 2 to take into account changes and differences in fracture and matrix pore volume compressibilities in naturally fractured reservoirs.
TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractThe Na Kika project, located in the deepwater Gulf of Mexico, is a unique development which ties-back six small to mediumsized oil and gas fields to the world's second deepest permanently moored production facility. Production from 12 subsea wells, in water depths ranging from 5800 to 7000 feet is routed to the production host through three flowline loops and one separate flowline. The project has been an economic and technological success. The application of intelligent well technology has enabled co-owners, Shell and BP, to successfully develop Na Kika with a minimum number of wells, and continues to help provide world-class reservoir surveillance data and ensure high standards of reservoir management.The fields are in a complex deepwater turbidite environment. Many of the reservoirs are highly faulted and compartmentalized due to salt movement, and several extend beneath salt structures and are difficult to image. Permanent downhole pressure and temperature sensors have been installed in all Na Kika wells. Additionally, four wells have been completed with interval control valves (ICVs) to enable 11 separate stacked reservoirs in two complex fields to be concurrently depleted.Intelligent well technology has provided dynamic performance data at the reservoir level that has been critical to improving reservoir characterization, reducing forecast uncertainty and enabled the operator to optimize production offtake. Downhole sensors provide well performance information such as permeability, skin and productivity index, on a real-time basis. Bottomhole pressure buildup (PBU) data are available on most well closures and have helped characterize reservoir barriers, zones of changing fluid mobility and levels of aquifer support. ICVs have enabled well testing at the reservoir level in multi-zone wells and have improved production allocation. This paper demonstrates how these surveillance data have been used to improve reservoir management and decision making.
The Na Kika project, located in the deepwater Gulf of Mexico, is a unique development which ties-back six small to medium-sized oil and gas fields to the world's second deepest permanently moored production facility. Production from 12 subsea wells, in water depths ranging from 5800 to 7000 feet is routed to the production host through three flowline loops and one separate flowline. The project has been an economic and technological success. The application of intelligent well technology has enabled co-owners, Shell and BP, to successfully develop Na Kika with a minimum number of wells, and continues to help provide world-class reservoir surveillance data and ensure high standards of reservoir management. The fields are in a complex deepwater turbidite environment. Many of the reservoirs are highly faulted and compartmentalized due to salt movement, and several extend beneath salt structures and are difficult to image. Permanent downhole pressure and temperature sensors have been installed in all Na Kika wells. Additionally, four wells have been completed with interval control valves (ICVs) to enable 11 separate stacked reservoirs in two complex fields to be concurrently depleted. Intelligent well technology has provided dynamic performance data at the reservoir level that has been critical to improving reservoir characterization, reducing forecast uncertainty and enabled the operator to optimize production offtake. Downhole sensors provide well performance information such as permeability, skin and productivity index, on a real-time basis. Bottomhole pressure buildup (PBU) data are available on most well closures and have helped characterize reservoir barriers, zones of changing fluid mobility and levels of aquifer support. ICVs have enabled well testing at the reservoir level in multi-zone wells and have improved production allocation. This paper demonstrates how these surveillance data have been used to improve reservoir management and decision making. Introduction The Na Kika development is located in the Mississippi Canyon (MC) area in the deepwater Gulf of Mexico, USA, approximately 140 miles southeast of New Orleans and 60 miles offshore (Fig. 1). The Na Kika project consists of a semi-submersible production system connected via flow lines and umbilicals to six remote fields (Fig. 2). The non-drilling platform is located in MC block 474. Fig. 1 Na Kika location map. Reservoir sands in Na Kika typically have good to excellent rock quality, with porosity generally averaging 30% or more and permeability ranging between 100 to 1000 md. Gross thickness of the individual reservoirs ranges from 25 to 300 ft. Net to gross ratios are high (0.9) in the sheet-like deposits, low (0.2–0.4) in the thin-bedded levee; and ranges from 0.4 to 0.6 in the hybrid channel-levee deposits. Ariel and Fourier fields feature multiple stacked reservoirs which required multiple-completion wells to make Na Kika an economic project. Differential pressure, crossflow, or early water breakthrough were the main risks identified with producing multiple-completion wells that might lead to costly well interventions (Glandt 2005).
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