Pressure data filtering and horizontal well test analysis case study

1997 ◽  
Author(s):  
Magdy S. Osman ◽  
G. Stewart
Keyword(s):  
Horizontal Well ◽  
Well Test ◽  
Data Filtering ◽  
Pressure Data ◽  
Well Test Analysis ◽  
Test Analysis

Practical Application of Pressure-Rate Deconvolution to Analysis of Real Well Tests

2005 ◽  
Vol 8 (02) ◽  
pp. 113-121 ◽  
Author(s):  
Michael M. Levitan
Keyword(s):  
Test Data ◽  
Rate Data ◽  
Well Test ◽  
Pressure Data ◽  
Well Test Analysis ◽  
Test Analysis ◽  
Deconvolution Algorithm ◽  
Constant Rate ◽  
Test Pressure ◽  
Real Test

Summary Pressure/rate deconvolution is a long-standing problem of well-test analysis that has been the subject of research by a number of authors. A variety of different deconvolution algorithms have been proposed in the literature. However, none of them is robust enough to be implemented in the commercial well-test-analysis software used most widely in the industry. Recently, vonSchroeter et al.1,2 published a deconvolution algorithm that has been shown to work even when a reasonable level of noise is present in the test pressure and rate data. In our independent evaluation of the algorithm, we have found that it works well on consistent sets of pressure and rate data. It fails, however, when used with inconsistent data. Some degree of inconsistency is normally present in real test data. In this paper, we describe the enhancements of the deconvolution algorithm that allow it to be used reliably with real test data. We demonstrate the application of pressure/rate deconvolution analysis to several real test examples. Introduction The well bottomhole-pressure behavior in response to a constant-rate flow test is a characteristic response function of the reservoir/well system. The constant-rate pressure-transient response depends on such reservoir and well properties as permeability, large-scale reservoir heterogeneities, and well damage (skin factor). It also depends on the reservoir flow geometry defined by the geometry of well completion and by reservoir boundaries. Hence, these reservoir and well characteristics are reflected in the system's constant-rate drawdown pressure-transient response, and some of these reservoir and well characteristics may potentially be recovered from the response function by conventional methods of well-test analysis. Direct measurement of constant-rate transient-pressure response does not normally yield good-quality data because of our inability to accurately control rates and because the well pressure is very sensitive to rate variations. For this reason, typical well tests are not single-rate, but variable-rate, tests. A well-test sequence normally includes several flow periods. During one or more of these flow periods, the well is shut in. Often, only the pressure data acquired during shut-in periods have the quality required for pressure-transient analysis. The pressure behavior during the individual flow period of a multirate test sequence depends on the flow history before this flow period. Hence, it is not the same as a constant-rate system-response function. The well-test-analysis theory that evolved over the past 50 years has been built around the idea of applying a special time transform to the test pressure data so that the pressure behavior during individual flow periods would be similar in some way to constant-rate drawdown-pressure behavior. The superposition-time transform commonly used for this purpose does not completely remove all effects of previous rate variation. There are sometimes residual superposition effects left, and this often complicates test analysis. An alternative approach is to convert the pressure data acquired during a variable-rate test to equivalent pressure data that would have been obtained if the well flowed at constant rate for the duration of the whole test. This is the pressure/rate deconvolution problem. Pressure/rate deconvolution has been a subject of research by a number of authors over the past 40 years. Pressure/rate deconvolution reduces to the solution of an integral equation. The kernel and the right side of the equation are given by the rate and the pressure data acquired during a test. This problem is ill conditioned, meaning that small changes in input (test pressure and rates) lead to large changes in output result—a deconvolved constant-rate pressure response. The ill-conditioned nature of the pressure/rate deconvolution problem, combined with errors always present in the test rate and pressure data, makes the problem highly unstable. A variety of different deconvolution algorithms have been proposed in the literature.3–8 However, none of them is robust enough to be implemented in the commercial well-test-analysis software used most widely in the industry. Recently, von Schroeter et al.1,2 published a deconvolution algorithm that has been shown to work when a reasonable level of noise is present in test pressure and rate data. In our independent implementation and evaluation of the algorithm, we have found that it works well on consistent sets of pressure and rate data. It fails, however, when used with inconsistent data. Examples of such inconsistencies include wellbore storage or skin factor changing during a well-test sequence. Some degree of inconsistency is almost always present in real test data. Therefore, the deconvolution algorithm in the form described in the references cited cannot work reliably with real test data. In this paper, we describe the enhancements of the deconvolution algorithm that allow it to be used reliably with real test data. We demonstrate application of the pressure/rate deconvolution analysis to several real test examples.

Analysis of Horizontal-Well Responses: Contemporary vs. Conventional

2001 ◽  
Vol 4 (04) ◽  
pp. 260-269 ◽  
Author(s):  
Erdal Ozkan
Keyword(s):  
Horizontal Well ◽  
Horizontal Wells ◽  
Well Test ◽  
Transient Pressure ◽  
Vertical Wells ◽  
Well Test Analysis ◽  
Test Analysis ◽  
Response Models ◽  
In The Beginning ◽  
Well Models

Summary Most of the conventional horizontal-well transient-response models were developed during the 1980's. These models visualized horizontal wells as vertical wells rotated 90°. In the beginning of the 1990's, it was realized that horizontal wells deserve genuine models and concepts. Wellbore conductivity, nonuniform skin effect, selective completion, and multiple laterals are a few of the new concepts. Although well-established analysis procedures are yet to be developed, some contemporary horizontal-well models are now available. The contemporary models, however, are generally sophisticated. The basic objective of this paper is to answer two important questions:When should we use the contemporary models? andHow much error do we make by using the conventional models? This objective is accomplished by considering examples and comparing the results of the contemporary and conventional approaches. Introduction Since the early 1980's, horizontal wells have been extremely popular in the oil industry and have gained an impeccable standing among the conventional well completions. The rapid increase in the applications of horizontal-well technology brought an impetuous development of the procedures to evaluate the performances of horizontal wells. These procedures, however, used the vertical-well concepts almost indiscriminately to analyze the horizontal-well transient-pressure responses.1–14 Among these concepts were 1) the assumptions of a line-source well and an infinite-conductivity wellbore, 2) a single lateral withdrawing fluids along its entire length, and 3) a skin region that is uniformly distributed along the well. It should be realized that for the lengths, production rates, and configurations of horizontal wells drilled in the 1980's, these concepts were usually justifiable. The increased lengths of horizontal wells, high production rates, sectional and multilateral completions, and the vast variety of other new applications toward the end of the 1980's made us question the validity of the horizontal-well models and the well-test concepts adopted from vertical wells. The interest in improved horizontal-well models also flourished on the grounds of high productivities of horizontal wells. It was realized that, in many cases, a few percent of the production rate of a reasonably long horizontal well could amount to the cumulative production rate of a few vertical wells. In addition, the productivity-reducing effects were additive; that is, a slight reduction in the productivity here and there could add up to a sizeable loss of the well's production capacity. Furthermore, the low oil prices also created an economic environment where the marginal gains and losses in the productivity may decisively affect the economics of many projects. In the beginning of the 1990's, a new wave of developing horizontal-well solutions under more realistic conditions gained impetus.15–25 As a result, some contemporary models are available today for those who want to challenge the limitations of the conventional horizontal-well models. Unfortunately, the rigor is accomplished at the expense of complexity. Furthermore, even when a rigorous model is available, well-established analysis procedures are usually yet to be developed. This paper presents a critique of the conventional and contemporary horizontal well-test-analysis procedures. The main objective of this assessment is to answer the two fundamental questions horizontal-well-test analysts are currently facing:When is the use of contemporary analysis methods essential? andIf the conventional analysis methods are used, what are the margins of error? Background: The Conventional Methods The standard models of horizontal-well-test analysis have been developed mostly during the 1980's.1-4,8,9 Despite the differences in the development of these models, the basic assumptions and the final solutions are similar. Fig. 1 is a sketch of the horizontal well-reservoir system considered in the pressure-transient-response models. A horizontal well of length Lh is assumed to be located in an infinite slab reservoir of thickness h. The elevation of the horizontal well from the bottom boundary of the formation (well eccentricity) is denoted by zw. The top and bottom reservoir boundaries are usually assumed to be impermeable, although some models consider constant-pressure boundaries.14,15 Before discussing the characteristic features of the conventional horizontal-well transient-pressure-response models, we must first define the dimensionless variables to be used in our discussion. We define the dimensionless pressure, time, and distance in the conventional manner except that we use the horizontal-well half-length, Lh/2, as the reference length in the system. These variables are defined, respectively, by the following expressions.Equation 1Equation 2Equation 3Equation 4 In Eqs. 1 through 3, k=the harmonic average of the principal permeabilities that are assumed to be in the directions of the coordinate axes (). We also define the dimensionless horizontal-well length, wellbore radius, and well eccentricity (distance from the bottom boundary of the formation) as follows.Equation 5Equation 6Equation 7 In Eq. 6, rw, eq=the equivalent radius of the horizontal well in an anisotropic reservoir.26

Case Study Well Test Analysis on Gas Well in Basement Granite Reservoir of South Sumatera

2019 ◽  
Author(s):  
Dimas Panji Laksana ◽  
Ratnayu Sitaresmi ◽  
Hari Karyadi Oetomo ◽  
Arditya Puspiantoro
Keyword(s):  
Well Test ◽  
Well Test Analysis ◽  
Test Analysis ◽  
Gas Well
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