A Practical Nonlinear Regression Technique for Horizontal Well Test Interpretation

2005 ◽  
Vol 23 (3-4) ◽  
pp. 341-369 ◽  
Author(s):  
Yueming Cheng ◽  
Duane A. McVay ◽  
W. John Lee
Keyword(s):  
Nonlinear Regression ◽  
Horizontal Well ◽  
Regression Technique ◽  
Test Interpretation ◽  
Well Test

Well Test Interpretation Method of Horizontal Well in Stress-Sensitive Gas Reservoir

2013 ◽  
Vol 295-298 ◽  
pp. 3183-3191
Author(s):  
Xiang Yi Yi ◽  
Zhi Zhang ◽  
Cheng Yong Li ◽  
De Cai Li ◽  
Sheng Bo Wang
Keyword(s):  
Horizontal Well ◽  
Test Interpretation ◽  
Fractured Reservoir ◽  
Well Test ◽  
Gas Reservoir ◽  
Type Curve ◽  
Flow Through ◽  
Function Integration ◽  
Lord Kelvin ◽  
Interpretation Method

Stress-sensitive widely exists in fractured reservoir. In this paper, a mathematical model of flow in stress-sensitive reservoir with horizontal well is established based on experimental data and with process of linearization. By using of Lord Kelvin point-source solution, Bessel function integration and Poisson superimpose formula, the dimensionless pressure response function of horizontal well in infinite stress-sensitive reservoir is obtained. And then the derivative type curve is calculated. Based on the type curve, the characteristics and influencing factors of the fluid flow through porous medium of horizontal well in stress-sensitive gas reservoir are analyzed.

Robust Well-Test Interpretation by Using Nonlinear Regression With Parameter and Data Transformations

SPE Journal ◽  
2011 ◽  
Vol 16 (03) ◽  
pp. 698-712 ◽  
Author(s):  
Aysegul Dastan ◽  
Roland N. Horne
Keyword(s):  
Parameter Space ◽  
Nonlinear Regression ◽  
Wavelet Transformation ◽  
Data Sets ◽  
Wavelet Basis ◽  
Test Interpretation ◽  
Well Test ◽  
Reduced Basis ◽  
Data Set ◽  
Improved Performance

Summary Nonlinear regression is a well-established technique in well-test interpretation. However, this widely used technique is vulnerable to issues commonly observed in real data sets—specifically, sensitivity to noise, parameter uncertainty, and dependence on starting guess. In this paper, we show significant improvements in nonlinear regression by using transformations on the parameter space and the data space. Our techniques improve the accuracy of parameter estimation substantially. The techniques also provide faster convergence, reduced sensitivity to starting guesses, automatic noise reduction, and data compression. In the first part of the paper, we show, for the first time, that Cartesian parameter transformations are necessary for correct statistical representation of physical systems (e.g., the reservoir). Using true Cartesian parameters enables nonlinear regression to search for the optimal solution homogeneously on the entire parameter space, which results in faster convergence and increases the probability of convergence for a random starting guess. Nonlinear regression using Cartesian parameters also reveals inherent ambiguities in a data set, which may be left concealed when using existing techniques, leading to incorrect conclusions. We proposed suitable Cartesian transform pairs for common reservoir parameters and used a Monte Carlo technique to verify that the transform pairs generate Cartesian parameters. The second part of the paper discusses nonlinear regression using the wavelet transformation of the data set. The wavelet transformation is a process that can compress and denoise data automatically. We showed that only a few wavelet coefficients are sufficient for an improved performance and direct control of nonlinear regression. By using regression on a reduced wavelet basis rather than the original pressure data points, we achieved improved performance in terms of likelihood of convergence and narrower confidence intervals. The wavelet components in the reduced basis isolate the key contributors to the response and, hence, use only the relevant elements in the pressure-transient signal. We investigated four different wavelet strategies, which differ in the method of choosing a reduced wavelet basis. Combinations of the techniques discussed in this paper were used to analyze 20 data sets to find the technique or combination of techniques that works best with a particular data set. Using the appropriate combination of our techniques provides very robust and novel interpretation techniques, which will allow for reliable estimation of reservoir parameters using nonlinear regression.

Intelligent ESP System Enabled Effective Stimulation and Post-Treatment Well Test, A Case Study of Restoring Production from a Horizontal Well in Belayim Marine Field

2010 ◽  
Author(s):  
Rini Eka A Soegiyono ◽  
Mohamed Elsayed Ahmed Gatas Abuzeid ◽  
Mostafa M. El-Farahaty Osman ◽  
Ahmed ElSonbaty ◽  
A.M Guichard ◽  
...  
Keyword(s):  
Horizontal Well ◽  
Post Treatment ◽  
Well Test

Evaluating the Performance of Horizontal Multi-Frac Wells in a Depleted Gas Condensate Reservoir in Sultanate of Oman

2022 ◽  
Author(s):  
Josef R. Shaoul ◽  
Jason Park ◽  
Andrew Boucher ◽  
Inna Tkachuk ◽  
Cornelis Veeken ◽  
...  
Keyword(s):  
Horizontal Well ◽  
Horizontal Wells ◽  
Gas Condensate ◽  
Integrated Analysis ◽  
Single Fracture ◽  
Reservoir Pressure ◽  
Well Test ◽  
Vertical Wells ◽  
Fracture Conductivity ◽  
Half Length

Abstract The Saih Rawl gas condensate field has been producing for 20 years from multiple fractured vertical wells covering a very thick gross interval with varying reservoir permeability. After many years of production, the remaining reserves are mainly in the lowest permeability upper units. A pilot program using horizontal multi-frac wells was started in 2015, and five wells were drilled, stimulated and tested over a four-year period. The number of stages per horizontal well ranged from 6 to 14, but in all cases production was much less than expected based on the number of stages and the production from offset vertical wells producing from the same reservoir units with a single fracture. The scope of this paper is to describe the work that was performed to understand the reason for the lower than expected performance of the horizontal wells, how to improve the performance, and the implementation of those ideas in two additional horizontal wells completed in 2020. The study workflow was to perform an integrated analysis of fracturing, production and well test data, in order to history match all available data with a consistent reservoir description (permeability and fracture properties). Fracturing data included diagnostic injections (breakdown, step-rate test and minifrac) and main fracture treatments, where net pressure matching was performed. After closure analysis (ACA) was not possible in most cases due to low reservoir pressure and absence of downhole gauges. Post-fracture well test and production matching was performed using 3D reservoir simulation models including local grid refinement to capture fracture dimensions and conductivity. Based on simulation results, the effective propped fracture half-length seen in the post-frac production was extremely small, on the order of tens of meters, in some of the wells. In other wells, the effective fracture half-length was consistent with the created propped half-length, but the fracture conductivity was extremely small (finite conductivity fracture). The problems with the propped fractures appear to be related to a combination of poor proppant pack cleanup, low proppant concentration and small proppant diameter, compounded by low reservoir pressure which has a negative impact on proppant regained permeability after fracturing with crosslinked gel. Key conclusions from this study are that 1) using the same fracture design in a horizontal well with transverse fractures will not give the same result as in a vertical well in the same reservoir, 2) the effect of depletion on proppant pack cleanup in high temperature tight gas reservoirs appears to be very strong, requiring an adjustment in fracture design and proppant selection to achieve reasonable fracture conductivity, and 3) achieving sufficient effective propped length and height is key to economic production.

scholarly journals An approximation of behind-casing hydraulic conductivity between layers from transient pressure analysis

DYNA ◽  
2019 ◽  
Vol 86 (210) ◽  
pp. 108-114
Author(s):  
Freddy Humberto Escobar ◽  
Angela María Palomino ◽  
Alfredo Ghisays Ruiz
Keyword(s):  
Hydraulic Conductivity ◽  
Transient Analysis ◽  
Test Interpretation ◽  
Well Test ◽  
Transient Pressure ◽  
Pressure Transient Analysis ◽  
Pressure Transient ◽  
Transient Pressure Analysis ◽  
Pressure Analysis

Flow behind the casing has normally been identified and quantified using production logging tools. Very few applications of pressure transient analysis, which is much cheaper, have been devoted to determining compromised cemented zones. In this work, a methodology for a well test interpretation for determining conductivity behind the casing is developed. It provided good results with synthetic examples.

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