This paper was prepared for the 48th Annual Fall Meeting of the Society of Petroleum Engineers of AIME, to be held in Las Vegas, Nev., Sept. 30-Oct. 3, 1973. Permission to copy is restricted to an abstract of not more than 300 words. Illustrations may not be copied. The abstract should contain conspicuous acknowledgment of where and by whom the paper is presented. Publication elsewhere after publication in the JOURNAL OF PETROLEUM TECHNOLOGY or the SOCIETY OF PETROLEUM ENGINEERS JOURNAL is usually granted upon request to the Editor of the appropriate journal provided agreement to give proper credit is made.

Discussion of this paper is invited. Three copies of any discussion should be sent to the Society of Petroleum Engineers office. Such discussion may be presented at the above meeting and, with the paper, may be considered for publication in one of the two SPE magazines.

Abstract

Exxon's submerged production system (SPS) has successfully completed land tests. The SPS is a cluster of subsea wells and associated production controlling, separating and production controlling, separating and pumping equipment mounted on a subsea template pumping equipment mounted on a subsea template structure. The produced fluids are transported to surface processing facilities via pipelines to shore, to a platform or to a production riser which connects to a floating vessel. The subsea equipment is remotely controlled and monitored from the surface facilities by an electro-hydraulic supervisory control system. Pump down tools are used to service wellbore Pump down tools are used to service wellbore equipment and a manipulator operated from the surface is used to replace non-operative subsea equipment. All elements of the system have been designed and land tested. Work is in progress to perform an offshore test of the progress to perform an offshore test of the complete system.

The final suite of land tests on a prototype, 3-well, subsea production manifold prototype, 3-well, subsea production manifold and a maintenance manipulator were performed in a water-filled pit where the underwater production equipment was automatically operated production equipment was automatically operated to control well streams simulating liquid, gas-liquid, and sand laden production. In this testing, the prototype equipment met or exceeded design specifications. In addition, the maintenance manipulator was deployed from a surface vessel to a mock-up installation in 425 feet of water to demonstrate its ability to land on its track which surrounds the underwater equipment. This deployment test, when coupled with the pit test, proved the manipulator to be capable of performing the maintenance tasks. Results of tests on the SPS wellbore equipment and on a pre-prototype pump/separator subsystem have indicated the utility of these equipment subsystems in performing their functions. Tests simulating operating conditions have permitted an evaluation and selection of pressure swivels and hoses for the production riser. Land tests of line-up techniques production riser. Land tests of line-up techniques and remote pipeline connectors have permitted the design of prototype pipeline connecting equipment needed for the SPS. The planned offshore test of the SPS will provide a comprehensive evaluation of equipment and procedures and, hence, demonstrate the potential utility of the SPS in deepwater applications.

American Institute of Mining, Metallurgical, and Petroleum Engineers, Inc.

Abstract

Offshore installation of Exxon's Submerged Production System (SPS) is nearing completion. Production System (SPS) is nearing completion. The pilot test which is being performed in the West Delta Block 73 Field in the Gulf of Mexico will have all of the equipment elements necessary to develop and produce deepwater oil reserves. Furthermore, the pilot test procedures for installing, operating, and procedures for installing, operating, and maintaining the underwater equipment and wells are applicable to deepwater use. The test will provide information to verify equipment design, provide information to verify equipment design, evaluate installation and maintenance procedures and assess operating performance of the SPS.

The equipment manufacturing phase of the test is essentially complete; only the final assembly of the production riser remains. A substantial amount of novel equipment has been manufactured, assembled and tested. This effort required 15 calendar months before offshore installation could start. Although numerous problems were encountered, lack of adequate quality control at all levels of manufacturing required the most effort to correct. The entire land phase operation was geared to finding and correcting problems before the equipment went offshore. problems before the equipment went offshore. The offshore installation phase is about 85 percent complete. A large amount of this work percent complete. A large amount of this work has been performed using atypical if not unique procedures. Two structures have been installed procedures. Two structures have been installed on the seabed. Three wells have been drilled, five pipelines laid and connected, two electric cables laid and connected, and production and control facilities installed on an existing platform. Although unexpected problems have platform. Although unexpected problems have been encountered, they were solved using techniques suitable for deepwater. Some areas where improvements in equipment performance and reduction in installation costs can be achieved have been identified. It is much too early to reach firm value judgments on the overall system; however, the test goals are being achieved and the results to date bolster our confidence that truly deepwater oil reserves are within reach of present production technology.

Introduction

This paper is a progress report on the evaluation of a Submerged Production System (SPS) for producing deepwater oil reserves. In a previous producing deepwater oil reserves. In a previous paper, the system was described in some detail paper, the system was described in some detail and the results of extensive land tests were presented. The subject of this paper is the presented. The subject of this paper is the fabrication of the prototype system and its installation in Exxon's West Delta Block 73 Field in the Gulf of Mexico.

For clarity, the elements of the SPS and a description of the pilot test installation are briefly reviewed in the following sentences. Figure 1 is a schematic representation of the pilot test installation in the production mode. pilot test installation in the production mode.

American Institute of Mining, Metallurgical, and Petroleum Engineers, Inc.

Abstract

Offshore installation of Exxon's prototype Submerged Production System is prototype Submerged Production System is nearing completion. This pilot test installation is being conducted in Exxon's West Delta 73 Field in the Gulf of Mexico. It includes the equipment necessary to develop and produce deep water oil reserves. This pilot test should provide the information necessary to verify provide the information necessary to verify equipment designs, as well as deep water installation, operating, and maintenance procedures. The program thus far has procedures. The program thus far has included the seafloor installation of two large pile-founded structures (a drilling and production template and a marine production riser base), installation of two production riser base), installation of two subsea booster pumps on the template, and drilling and completion of three directional wells which have been connected to the subsea manifold. All five pipelines and the two electric cables required have been laid and connected to establish necessary communications between the template, riser base, and surface production facilities located on a nearby platform. Finally, remote maintenance procedures and tools have been used to perform maintenance tasks on the subsea equipment. The system is currently being brought up to operational status.

While most of the equipment and procedures have proven satisfactory, numerous procedures have proven satisfactory, numerous unexpected problems have been encountered. These have been solved using techniques applicable to deep water operations. Improvements are needed in some areas to reduce installation costs and increase equipment performance. Our experience to date continues to generate confidence that deep water oil reserves are within reach of current technology and the problems attendant with the use of complex equipment in a remote environment can be satisfactorily overcome.

Introduction

This paper updates progress of the offshore activities of the SPS pilot installation. Previous papers described the system in detail and discussed the fabrication of a prototype system and its offshore installation in Exxon's West Delta Block 73 Field in the Gulf of Mexico.

To facilitate the review of this paper by readers who do not have access to the previous papers, elements of the SPS and previous papers, elements of the SPS and the pilot test installation are briefly described in the following paragraph.

Abstract

This paper describes the results and interpretation of a large-scale laboratory sand production test. In the experiment, a real well with multiple perforations was simulated, using an outcrop rock selected to represent core material from a specific field. The objective of the experiment, which was the first of its kind, was to investigate the influence of both effective stress increase and drawdown on sand production behavior, taking into account the influence of the presence of casing and cement and of perforating. An additional objective of the test was to investigate the influence of a water cut on the sand produced. The laboratory well behaved very realistically, in terms of both oil and sand production.

Introduction

Reliable predictions of sand production potential are required to make realistic sand production management and contingency planning possible. Unnecessary application of sand exclusion measures results in increased completion costs and considerable loss of well productivities. Further, sand prediction may assist in selecting the most attractive sand control techniques [1].

Although, over the years, a large number of conceptual, analytical and numerical models for sand production prediction have been developed, see e.g. [2-10], the value of these models may still be questioned, considering the discrepancy observed between the model predictions and field observations. To improve and validate the sand prediction models, reliable sand production data are indispensable. The sand production data available can be divided into laboratory sand production test data and field sand production data collected from real wells. Laboratory sand production tests typically concern small-scale simulation of flow through perforations or cylindrical cavities in stressed cylindrical samples (see e.g.[11]). Advantages of such laboratory tests include the controlled stress and pressure boundary conditions, the extensive monitoring facilities available and the simple geometry used, which facilitates interpretation of the experiments. Field observations involve far more complex situations (e.g. perforation interaction), with many uncertainties concerning the actual downhole situation and only limited possibilities of imposing prescribed boundary conditions. Nevertheless, interpreting and predicting such field observations are the prime objective of sand prediction modeling.

P. 325^

SPE Members

Abstract

Using well test analytical solutions for production prediction is rarely done. as this seems to be abstract and to require assumptions that are not very physical. But it presents a good alternative to numerical simulation, which is often expensive and cumbersome, and to decline-curve analysis, which has little theoretical justification in complicated cases.

This paper presents existing methods, and generalizes them to "n" wells in the reservoir. This allows the prediction of the flowrate produced for a given pressure drop history and a given global drainage area. but without a priori knowledge of the drainage area of each well. This is especially useful in reservoir monitoring.

This work shows how changes in the imposed pressure drop can be treated, which is straightforward. as it does not affect the reservoir response. But it also shows how nonlinearities. i.e. changes in the well or reservoir themselves can be treated. To some extent this technique allows modelling phenomena which are non linear. but still classic during the life of a well: fracturing. damage. or change in skin due to the appearance of multiphase flow.

This technique thus broadens the applicability of analytical production prediction.

Introduction

Usually, production prediction is performed in an empirical way. mainly by analysing decline curves (exponential. harmonic or more generally hyperbolic). These have little theoretical justification. other than in very simple cases. The other alternative is to run full-field gridded simulators. which give accurate results, but which need both complicated algorithms. and numerical know-how to be used.

This paper presents an intermediate approach. as it describes an analytical method to predict production in a more rigorous manner than decline-curve analysis but simpler than with a numerical simulator. Since it can be done with a well testing software.

This approach uses the theory of Laplace transforms described by Everdingen and Hurst namely that the kernel functions already used in well testing for pressure can also be defined for the flowrate, as dynamic productivity indexes. They are generalized for multiple well interference, which, to our knowledge, could be done only iteratively until now.

The technique yields accurate results for production prediction. both for the short-term transients and the long-term behavior, when the flowing pressures only are known in advance. No assumption on the individual drainage radius of any well has to be made, since the interference is quantified exactly.

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This paper was prepared lor presentatiOn at OHshore Europe 87. The abstract should contain conspicuous acknowledgement of where and by whom the paper was presented. Publication elsewhere is usually granted upon request provided proper credit is made. SUMMARY The high rate production test performed by Norsk Hydro on the Troll East structure during the summer of 1985 with the semi submersible drilling rig Treasure Seeker required that a large number of specially designed, modified or adapted equipment items were used in order to fulfil the test objectives and maintain safe operations. These were: Jetting tool for casing cleaning. Gravel pack floor manifold to ease operations.

Summary. The estimation of reservoir properties from production or pressure data measured during production or well tests is an important process for reservoir characterization and performance prediction. A key step in that process is the selection of a reservoir model for use in the interpretation of the data. We develop a procedure for selecting the most appropriate model from a pool of candidates. A parameter estimation algorithm is used to evaluate parameters within candidate models. Statistical measures are then used to select the most appropriate model.

We demonstrate our procedure for model selection with actual well test data and production data from the Devonian shale. We show how our methodology can be used to evaluate whether certain reservoir features can be identified from measured production or pressure data. We also present a test for evaluating whether independent estimates of reservoir properties are consistent with measured pressure and production data.

Introduction

Production or pressure data measured at wells during reservoir production or well tests are significant sources of information for estimating reservoir properties to predict future reservoir performance. Two key steps in the process for estimating reservoir properties from pressure/production data are selection of an appropriate reservoir model and estimation of parameters within that model.

The latter step has received much attention in the literature. A number of automatic history-matching (or parameter-estimation) algorithms have been proposed for that purpose. Type curve and other graphic methods are also available for estimating parameters for selected reservoir models. Perhaps more difficult, but no less important, is the selection of the most appropriate reservoir model. Generally, this requires first selecting the appropriate set of material and energy balances for the physical processes involved, as well as the fluid properties and reservoir geometry. Then, the reservoir properties must be chosen. These properties may vary significantly with location in the reservoir. However, we cannot expect to estimate those properties accurately throughout the reservoir on the basis of the limited data usually available. Instead, we usually parameterize the unknown properties in a way that is consistent with geologic data and other data from the reservoir so that fewer unknown parameters need be established on the basis of the pressure/production data. A common method of parameterization is zonation, for which reservoir properties are assumed to be uniform throughout various regions of the reservoir. As we use "model" to refer to the set of equations that relate the reservoir parameters to the dependent, or simulated, quantities, different parameterizations correspond to different reservoir models.

Here we consider situations for which the measured pressure/production data may be explained adequately with reservoir models containing relatively few unknown parameters. Specifically, we deal with reservoir models in which the unknown properties are assumed to be uniform; our method for model selection is not limited, however, to such situations. We do not deal specifically with selection of appropriate material and energy balances or fluid properties; these rather broad topics are addressed in a number of texts (e.g., see Refs. 1 through 3). We develop a systematic, quantitative method for choosing from among candidate reservoir models the most appropriate model for a given set of pressure/production data.

We illustrate the importance of model selection for the accuracy of estimates of the reservoir properties. We also demonstrate how our method for model selection can be used to establish whether a given set of measured data is sufficient for identifying certain reservoir features. For example, it can be used to ascertain whether sufficient data have been measured to determine boundary effects, skin, or the presence of more than a single-porosity system. Thus, our method can be used to quantify the information about reservoir properties that is "contained" in the measured data.

Model Selection

A key difficulty in choosing the most appropriate reservoir model is that several different reservoir descriptions (or models) may apparently satisfy the available information about the reservoir. That is, the models may be consistent with available geological and petrophysical information and seem to provide more or less equivalent matches of the measured pressure/production data. The issue may be further complicated when type curve or other graphic methods are used to evaluate the parameters within a given model because different sets of parameters may provide matches of different precision corresponding to different regions of the data. That is, no "perfect" matches can be expected because of the finite accuracy of the measurements and simplified nature of the models, so the best compromise in matching the data is not at all apparent.

This latter consideration can often be alleviated when parameter estimation methods are used. Proper formulation of the performance index can lead to a unique set of estimates that may be called best (in a certain sense discussed in more detail later) provided that the proper reservoir model is selected. Thus, we believe a method for selecting the most appropriate reservoir model for use in conjunction with parameter estimation methods is a particularly attractive method for analyzing reservoir production or well test data.

We have developed a method to choose, on the basis of measured pressure/production data, the most appropriate reservoir model (or reservoir description) from among a set of candidate reservoir models. A pool of candidate models that are consistent with all available information about the reservoir is to be determined. We then use statistical measures to choose the most appropriate model from among these candidates.

As discussed later, the pool of candidates may be formed as a hierarchy of models, as determined by the most complete model (in the sense of the greatest number of unknown parameters) that the engineer believes is necessary for describing the reservoir. The hierarchy is characterized by increasing numbers of unknown parameters. It is important that at least one model satisfactorily describes (or "explains") the data (it is sufficient that the most complete model does so). This can generally be established satisfactorily by examination of a plot of the differences between the observed data and the corresponding quantities simulated with parameters obtained from a history match of the data.

SPEFE

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Abstract
A novel well-test for in situ estimation of relative permeabilities was recently proposed. This test consists of three periods, (i) injection of water into an oil reservoir, (ii) a falloff test and (iii) a producing period. The producing
period is critical as it yields production data that reflects changes in sandface mobility and is thus highly sensitive to the parameters used to model relative permeability curves. A major shortcoming of the data analysis procedure proposed in previous work was that it required a numerical reservoir simulator for matching pressure data. In this work, based on Buckley-Leverett theory and ideas from a front tracking method, we derive an approximate analytical solution for the pressure response during an injection/falloff/production test (IFPT) by applying on the Thompson-Reynolds steady-state theory. By matching data to the analytical solution by minimization of a weighted least squares objective function, we generate estimates of absolute permeability, relative permeabilities and the well skin factor. We show the method can be applied with either power law models or B-splines.

Introduction
Beginning at least as early as 1952 (Verigin¹), various analytical or approximate analytical solutions for the pressure response during injection and/or falloff tests have been presented in the literature. In general, these solutions require a model for generating the saturation distribution as a function of time (piston displacement of Buckley-Leverett) during injection and assume that the front does not move during falloff so that the falloff solution is equivalent
to solving a multicomposite single-phase reservoir problem where the pressure at the end of the injection solution period provides the initial condition for the falloff problem. Abbaszadeh and Kamal² show that the pressure solution at the end of injection can itself be obtained from an equivalent multicomposite problem, whereas, Bratvold and Horne³ assume the validity of the Boltzman transform to generate the injection solution. Most solutions available
consider only injection at a constant rate followed by a falloff test, the major exception being the work of Levitan⁴ who was able to generate a solution for multirate tests. Most solutions, including all those mentioned above, consider only one-dimensional radial flow problems, the major exceptions being Thambynayagam⁵ who presented injection/falloff solutions for a vertical restricted-entry well assuming piston displacement recent papers^6,7,8 which used the Thompson-Reynolds steady-state theory^9,10 to generate approximate analytical solutions for complete penetration
and restricted-entry vertical wells as well as for horizontal wells.

Peres and Reynolds⁶ showed that incorporation of the skin factor using the infinitesimally thin skin is invalid during the injection period; for example, for one-dimensional radial flow problems, they showed that a skin zone with a width of a few inches can have a pronounced effect on the injection pressure and its derivative for several hours. For a damaged well and an unfavorable mobility ratio, they showed that the injection pressure derivative may be negative for a considerable period of time. Because of this result, we use a finite-radius skin zone¹¹ for the injection/falloff/production test (IFPT) considered here.

Description: As a paper of the MH21 study, this paper describes the design and operation of the surface flow test system utilized for the 1st Offshore Production Test of Methane Hydrate in deep water offshore Japan in March 2013 using a dynamically positioned drill ship. The unique characteristics of this production test required a customized approach to the design of this system. As the production test was carried out for scientific research purposes, the data acquisition requirements were of paramount importance.
Application: The information contained in this paper can be applied to future offshore production tests of methane hydrate using the depressurization technique.
Results, Observations, and Conclusions:
The surface flow test system was successfully designed, installed, commissioned and operated. Measurement and separation of the produced gas and water were effectively achieved under low temperature,
low pressure, and low production rate conditions. Transportation and operation of surface flow test equipment was able to accommodate the motions of the floating drilling vessel. Two separate fluid processing trains were installed for high quality measurement of the gas and water rates. A real time data sharing system to monitor the condition of the surface system and the down hole systems implemented but shut down of the downhole equipment was not triggered automatically by surface production equipment ESD. Some non-critical data acquisition failures occurred or limitations observed during the production test.
Significance of Subject Matter: It is believed that this was the first offshore production test of methane hydrate to have been conducted in the world. The design philosophy and operational experience will be useful for future production testing in similar environments.