Harmonic pulse testing for gas well deliverability assessment

Harmonic Pulse Testing was introduced in the early 1970’s as a special case of pulse testing. It is characterized by a periodic variation of production/injection rate. Subsequent developments proved that it could provide the same information as a conventional well test (permeability and skin, heterogeneity) in addition to those given by a pulse test (areal connectivity within the reservoir) if proper interpretation models were adopted. Consequently, it can be considered as a promising methodology to test a well during ongoing field operations without stopping production and thus it is very attractive for monitoring well performance, especially of gas storage wells. Initially applied to oil wells, Harmonic Pulse Testing has recently been extended to gas wells for which the assumption of Darcy flow regime is no longer valid because of inertial phenomena and/or turbulence. Harmonic Pulse Testing for gas wells comprises three or more consecutive sequences of pulses characterized by increasing average rate, similar to a Flow After Flow test. The interpretation of a single-well Harmonic Pulse test is based on the derivative approach in the frequency domain to obtain kh and the skin components (mechanical skin and D factor). The possibility of assessing well deliverability from a multi-sequence pulse test was analysed in the research work presented in this paper. Different Pulse test configurations were considered and compared with the well-established Flow After Flow test in terms of deliverability estimate. To this end synthetic well test data were generated and sensitivity to test design, well parameters and reservoir interference were carried out. Results show that multi-sequence pulse tests can be used to obtain the well deliverability of a gas well with the advantage that both the tested well and the neighboring wells needn’t be shut-in prior to or during the test.

Harmonic Pulse Testing was introduced in the early 1970’s as a special case of pulse testing. It is characterized by a periodic variation of production/injection rate. Subsequent developments proved that it could provide the same information as a conventional well test (permeability and skin, heterogeneity) in addition to those given by a pulse test (areal connectivity within the reservoir) if proper interpretation models were adopted. Consequently, it can be considered as a promising methodology to test a well during ongoing field operations without stopping production and thus it is very attractive for monitoring well performance, especially of gas storage wells. Initially applied to oil wells, Harmonic Pulse Testing has recently been extended to gas wells for which the assumption of Darcy flow regime is no longer valid because of inertial phenomena and/or turbulence. Harmonic Pulse Testing for gas wells comprises three or more consecutive sequences of pulses characterized by increasing average rate, similar to a Flow After Flow test. The interpretation of a single-well Harmonic Pulse test is based on the derivative approach in the frequency domain to obtain kh and the skin components (mechanical skin and D factor). The possibility of assessing well deliverability from a multi-sequence pulse test was analysed in the research work presented in this paper. Different Pulse test configurations were considered and compared with the well-established Flow After Flow test in terms of deliverability estimate. To this end synthetic well test data were generated and sensitivity to test design, well parameters and reservoir interference were carried out. Results show that multi-sequence pulse tests can be used to obtain the well deliverability of a gas well with the advantage that both the tested well and the neighboring wells needn’t be shut-in prior to or during the test.


ISSN 1121-9041

CiteScore:
2020: 3.8
CiteScore measures the average citations received per peer-reviewed document published in this title.
CiteScore values are based on citation counts in a range of four years (e.g. 2016-2019) to peer-reviewed documents (articles, reviews, conference papers, data papers and book chapters) published in the same four calendar years, divided by the number of these documents in these same four years (e.g. 2016 —19).
Source Normalized Impact per Paper (SNIP):
2019: 1.307
SNIP measures contextual citation impact by weighting citations based on the total number of citations in a subject field.
SCImago Journal Rank (SJR)
2019: o.657
SJR is a prestige metric based on the idea that not all citations are the same. SJR uses a similar algorithm as the Google page rank; it provides a quantitative and a qualitative measure of the journal's impact.
Journal Metrics: CiteScore: 1.0 , Source Normalized Impact per Paper (SNIP): 0.381 SCImago Journal Rank (SJR): 0.163

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