1. Masters of Science Thesis Defense
March 3, 2017| College Station, TX
Use of Rate Transient Analysis to Evaluate the Well Performance of A Mature Gas Field
Department of Petroleum Engineering
Texas A&M University
College Station, TX (USA)
Basayir Al-Lawati
Good Afternoon..
Today I am going to present my research which focuses on the use of rate transient analysis to evaluate the well performance of a mature gas field.
M.S. Defense | 07 March 2017
Texas A&M University | College Station, TX
Use of Rate Transient Analysis to Evaluate the Well Performance of A Mature Gas Field
Basayir Hussain AL-LAWATI

2. Project Rationale/ Objectives Orientation Methodology
Outline:
Project Rationale/ Objectives
Orientation
Methodology
Field Example — BHA Well 112
30-Year EUR Correlation Results
Parametric Correlation Results
Conclusions
I will start by describing the rationale for this work and some background information. Next, I will describe the methodology, then show you an analysis for a field example. Finally, I will share with you some of the results obtained from this work and I will end my presentation with my findings.
M.S. Defense | 07 March 2017
Texas A&M University | College Station, TX
Use of Rate Transient Analysis to Evaluate the Well Performance of A Mature Gas Field
Basayir Hussain AL-LAWATI

3. Project Rationale
Mismatch between observed reservoir performance and deterministic predictions have resulted in continuous revision of booked reserves.
Project Objectives:
Use "time-rate“ analysis (DCA: Decline Curve Analysis) and "time-rate-pressure" analysis (RTA: Rate Transient Analysis) to provide the following:
… an understanding of the reservoir potential of the BHA field.
… a comparison of reserves estimates from "time-rate" and "time-rate-pressure" methods.
… a correlation of reserves and reservoir property estimates.
The BHA field plays a significant role in Oman’s gas production as a nation. However’ production forecast and reserves estimation in field have shown considerable uncertainty due to the complexity and relatively low permeabilty. This has resulted in a mismatch between the observed reservoir performance and deterministic predictions resulting in continuous revisions of the booked reserves.
Therefore, in this work we will use both “time-rate”, also known as DCA and “time-rate-pressure” or rate transient analysis to…
Gain an understanding of the fields reservoir potential, comparison between the reserves estimation from both the time-rate and time-rate pressure methods, and finally a correlation of reserves and reseroir property estimates.
M.S. Defense | 07 March 2017
Texas A&M University | College Station, TX
Use of Rate Transient Analysis to Evaluate the Well Performance of A Mature Gas Field
Basayir Hussain AL-LAWATI

4. Orientation: Traditional "Time-Rate" Analysis (DCA)
"Loss Ratio" :
"Loss Ratio" Derivative:
Exponential (b=0)
Hyperbolic (0<b<1)
Harmonic (b=1)
‘Time-rate’ analysis or Arps hyperbolic decline relation has been traditionally used to estimate reserves. It is based on the loss ratio and loss ratio derivative which are used to describe the decline constant (D) and decline exponent (b) parameters. These relations are the basis for the parameters included in the hyperbolic relation. The b parameter for the hyperbolic relation is constant and should lie between 0 and 1.
The equation is exponential when the decline exponent is 0
Hyperbolic when the decline exponent is greater than 0 and less than 1
and harmonic, when b=1.
These relations don’t consider reservoir properties. They are only are applicable to BDF (rephrase).
In low permeability reservoirs, however, we observe extended transient linear flow periods.
Discussion:
Reservoir properties are not considered.
Applicable to boundary dominate flow (BDF)
M.S. Defense | 07 March 2017
Texas A&M University | College Station, TX
Use of Rate Transient Analysis to Evaluate the Well Performance of A Mature Gas Field
Basayir Hussain AL-LAWATI

5. Orientation: Modern "Time-Rate" Analysis (DCA)
Modified Hyperbolic (MH) (Robertson, 1988)
b is initially hyperbolic until a set Dlimit, after which D cannot decline and the equation becomes exponential.
Examined applicability of MH for b>1 to fit early transient data in low permeability reservoirs. (Seshadri and Mattar (2010))
Power-Law Exponential (PLE) (Ilk, 2008)
Developed to address tight gas/shale gas wells.
D-parameter exhibits a power-law behavior at early times and becomes constant at late times (per "D∞" term).
This model has the flexibility to model various flow regimes (transient, transition, and boundary-dominated flow (BDF)).
Modified-
Hyperbolic
Therefore in this work we use Modern ‘time-rate’ analysis: specifically, the MH and PLE. These methods have been proposed to match the early transient flow periods observed in low-permeabililty reservoirs.
The MH was introduced by Roberston in 1988, when he noticed that neither the exponential or hyperbolic is usually truly representative of actual production rates. The hyperbolic function is commonly applied to the early stages of production followed by an exponential tail. He therefore proposed, the MH, which is a piecewise function that allowed for application to different flow regimes where the decline constant is initially hyperbolic until a set Dlimit value, after which D is not allowed to decline and the equation switches to exponential decline.
Seshadri and Mattar (2010) examined the applicability of the MH when b>1 to fit the transient linear flow period for production data in low permeability reservoirs.
The power-law exponential relationship was introduced by Ilk et al. (2008). The relationship was introduced to specifically address tight gas or shale gas wells. His equation is a modification of the Arps exponential decline function and is derived from the observed behavior that the D-parameter (inverse o the loss ratio) exhibits: a decaying power-law behavior at early times and becomes constant at late times during BDF. It has flexibility to model transient, transition, and boundary-dominated flow regimes and is presented below.
MH: modification of arps hyperbolic model with an exponential tail
Captures early-time hyperbolic decline behavior
Avoids indefinite extrapoations of early-time behavior
PLE: empirical and based on power law behavior
Adequately represents transient and transition flow
Power-
Law
Exponential
M.S. Defense | 07 March 2017
Texas A&M University | College Station, TX
Use of Rate Transient Analysis to Evaluate the Well Performance of A Mature Gas Field
Basayir Hussain AL-LAWATI

6. Pseudopressure Drop-Normalized Pseudopressure Drop Function
Orientation: "Time-Rate-Pressure" Analysis (RTA)
Incorporates pressure into diagnostics and analysis.
Based in theory – valid for any flow regime.
Estimate reservoir properties and reservoir volume.
Analytical models can be validated using a numerical model.
"Blasingame" Plot
Pseudopressure Drop-Normalized
Rate Function
In addition to “time-rate” analysis, we also perform “time-rate-pressure” analysis, also known as RTA. RTA is unique in that it incorporates pressure to the analysis. It is based in theory and is valid for any flow regime… RTA enables estimation of reservoir properties and volume.
Two diagnostic plots are used in RTA: the “log-log” plot and the “blasingame” plot.
COME BACK
For rate transient analysis (RTA), the use of "diagnostic plots" such as the "Log-Log" and "Blasingame" plots provides meaningful insight about the behavior of a well. The Log-Log plot consists of flowrate-normalized pressure-drop (Dm(p)/qg) "integral" and the "integral derivative" functions plotted as against the material balance time function. We used cumulative gas production divided by gas flowrate to approximate the gas material balance time function, which is perfectly acceptable as we are using this for "diagnostics," not rigorous "analysis". We use these functions for visualizing the behavior of the production data. The analysis is performed by history matching the prescribed reservoir model to the production data functions.
The RTA methodology provides for analysis to be performed on both transient flow and boundary-dominated data. On the "Log-Log" plot, transient flow data are typically represented by a gently increasing trend (certain transient flow regimes have unique straight-line trends — e.g., linear flow behavior has a 1:2 slope trend). For boundary-dominated flow a 1:1 slope trend occurs at late times. The application of material balance time is particularly useful because this approach provides a constant-rate equivalent for variable flowrate/variable pressure drop data independent of the reservoir properties. (Palacio and Blasingame 1993).
In Fig. 6 we provide a schematic of the "Log-Log" plot (specifically the "integral derivative" function) where the different regimes can be observed. In Fig. 7, we present the "Log-Log" plot for BHA Well 087, both the (Dm(p)/qg) "integral" and the "integral derivative" data functions are shown (as symbols), as well as the model match (black lines). For the material balance time period of approximately 200-4,000 days, the (Dm(p)/qg) "integral" function suggests a 1:2 slope trend, which is indicative of an infinite conductivity vertical fracture. For the material balance time period > 4,000 hours an approximate 1:1 slope trend is observed, which confirms boundary-dominated flow behavior.
Similar to the "Log-Log" plot, the "Blasingame" plot uses (qg/Dm(p)) functions versus Gp/qg as alternate means of presenting and diagnosing data. In Fig. 8 we provide a schematic Blasingame plot which uses the rate "integral derivative" function to highlight various flow regimes. For reference, the "Blasingame" plot presents a (negative) unit slope during boundary-dominated flow. Transient flow features observed on the "Blasingame" plot depend on the nature of the prescribed reservoir model(s).
In Fig. 9 we present the "Blasingame" plot constructed for BHA Well 087 where all of the (qg/Dm(p)) functions are plotted versus Gp/qg. The "Blasingame" plot is somewhat more susceptible to data noise. Although the rate function (qg/Dm(p)) is typically less affected, the integral and integral derivative functions are often significantly affected by data noise. There are schemes to edit spurious data, but such schemes are not used in this work. As shown in Fig. 9, the (qg/Dm(p)) data function (red symbols) is fairly well-behaved, but the auxiliary functions are affected. The model match is actually quite good for the (qg/Dm(p)) function. And as noted, the auxiliary functions could be improved with judicious editing of the (qg/Dm(p)) data function (red symbols). For this work, we use the "Blasingame" plot as a check for the match of the data and model functions, and to validate certain flow regimes (e.g., linear flow and boundary-dominated flow).
"Log-Log" Plot
Rate-Normalized
Pseudopressure Drop Function
M.S. Defense | 07 March 2017
Texas A&M University | College Station, TX
Use of Rate Transient Analysis to Evaluate the Well Performance of A Mature Gas Field
Basayir Hussain AL-LAWATI

7. Orientation: Vertical well of finite- or infinite conductivity fracture
Formation-Linear Flow — Infinite conductivity fractures characterized by 1:2 slope.
Bilinear Flow — Finite conductivity fractures characterized by 1:4 slope.
Uniform-Flux Case — Uniform reservoir production per unit length of fracture characterized by 1:2 slope.
BHA wells are hydraulically fractured. Here we have some typical flow regimes observed in practice.
We have the formation….
Uniform flux case, which has a half slope, which is very similar to infinite conductivity case but assumes uniform reservoir production per unit length of fracture.
Wells in the BHA gas field are hydraulically fractured to enable economic production in this low-permeability reservoir. Hydraulically fractured have characteristic flow regimes based on the "conductivity" of the created vertical fractures. The typical cases observed in practice are:
● Infinite-conductivity fracture: Dimensionless fracture conductivity >100 (Lee 1996). Characterized by 1:2 slope on a log-log plot ("formation linear flow").
● Finite-conductivity fracture: Dimensionless fracture conductivity <10 (Lee 1996). Characterized by 1:4 slope on a log-log plot ("bilinear flow").
● Uniform flux fracture: Uniform reservoir production per unit length of fracture. Characterized by 1:2 slope on a log-log plot for higher values of time (essentially formation linear flow).
We therefore used diagnostic plots to estimate model parameters for a vertical well with either a finite or infinite conductivity.
M.S. Defense | 07 March 2017
Texas A&M University | College Station, TX
Use of Rate Transient Analysis to Evaluate the Well Performance of A Mature Gas Field
Basayir Hussain AL-LAWATI

8. Methodology: Wells selected based on continuity of production data.
Perform time-rate analysis (or DCA) using both the MH and PLE relations.
Perform time-rate-pressure analysis (or RTA) using diagnostic plots to estimate model parameters and then perform a simulation history match.
Generate a production forecast to estimate the cumulative production at 30 years as a proxy for EUR comparisons, for both the DCA and RTA methods.
Create correlations of the EUR results (DCA and RTA).
Create parametric correlations with the model parameters obtained for the DCA relations and the estimates of reservoir properties obtained from RTA.
We begin by selecting wells based on production continuity.
We perform time-rate analysis using both MH and PLE relations.
Next, we perform time-rate-pressure analysis using diagnostic plots to estimate model parameters. Once, the parameters are estimated we perform a simulation history match.
Production forecasts are then generated to estimate comulatvie production at 30 years as a proxy for EUR comparisons for both the DCA and RTA methods.
Finally, we create correlations of the EUR results with model parameters obtained for the DCA relations and estimates of reservoir properties obtained from RTA.
M.S. Defense | 07 March 2017
Texas A&M University | College Station, TX
Use of Rate Transient Analysis to Evaluate the Well Performance of A Mature Gas Field
Basayir Hussain AL-LAWATI

9. Analysis of Well Performance Field Example — BHA Well 112
I will demonstrate with a field example, BHA Well 112, how each of the 14 wells in this work was analyzed.
M.S. Defense | 07 March 2017
Texas A&M University | College Station, TX
Use of Rate Transient Analysis to Evaluate the Well Performance of A Mature Gas Field
Basayir Hussain AL-LAWATI

10. Field Example: Production History Plot1
1 — Significant noise present in the initial historical production period.
2 — Production against set choke.
3 — First-stage surface compression.
4 — Extended well shut-in.
5 — Surface compression (2nd and 3rd stages), resulting in improved production. 2 3 4 5
(talk about areas)
We begin by reviewing the historical production plot: we have the gas flow rate, marked by red circles and calculated bottomhole pressure (marked by blue square symbols) as a function of time on a Cartesian scale.
BHA Well 112 has been producing for 16 years.
Pressure data is initially noisy but becomes more consistent during the remainder of the production period.
We note that between 1500 and 3,700 days, calculated surface pressure is more or less constant, as the wells produces against a set choke pressure of ~2,000 psia.
At 3,700 days or in 2010, calculated bottomhole pressures decrease with the commissioning of Second stage compression in 2012.
The well experiences an extended shut-in period, after which..
Second and third stage compression is introduced at 4,800 and 5,700 days, respectively, resulting in further decreasing intake pressures. The gas flowrate stabilizes and continues to produce at a low declining rate.
Discussion:
BHA Well 112 has been on production for 16 years.
M.S. Defense | 07 March 2017
Texas A&M University | College Station, TX
Use of Rate Transient Analysis to Evaluate the Well Performance of A Mature Gas Field
Basayir Hussain AL-LAWATI

11. Field Example: Flowrate/Cumulative Production versus Time Plot
[1:1] Slope
(BDF)
Next, we plot the gas flowrates and cumulative production versus time on log-log scale. This is an "orientation plot" — our goal here is to observe specific flow regimes; and we note that we have placed a half-slope trend on this plot to indicate possible transient linear flow behavior which occurs at around ~200 to 3,000 days. We also overlay a unit slope line on the plot and based on the match, we think that the onset of BDF may begin at around 3,000 days. However, conclusion is speculative due to the erratic nature of the flowrate data.
Discussion:
Orientation plot — used to observe specific flow regime.
Possible "transient linear flow" behavior is observed (≈200-3,000 days).
Suspected BDF is observed ≈3,000 days.
Conclusion is speculative due to the erratic nature of the flowrate data.
M.S. Defense | 07 March 2017
Texas A&M University | College Station, TX
Use of Rate Transient Analysis to Evaluate the Well Performance of A Mature Gas Field
Basayir Hussain AL-LAWATI

12. Field Example: Diagnostic "Log-Log" Plot
" Pressure Function "
[1:1] Slope
(BDF)
[1:2] Slope
(Linear Flow)
" Pressure Integral-Derivative "
Diagnostic plots, the “log-log” plot on this slide and the “blasingame” plot in the next slide are used in RTA to determine the different flow regimes.
The Log-Log plot consists of flowrate-normalized pressure-drop (Dm(p)/qg) "integral" and the "integral derivative" functions plotted against the material balance time function.
We used cumulative gas production divided by gas flowrate to approximate the gas material balance time function, which is perfectly acceptable as we are using this for "diagnostics," not rigorous "analysis".
On the "Log-Log" plot, transient flow data are typically represented by a gently increasing trend (certain transient flow regimes have unique straight-line trends — e.g., linear flow behavior has a 1:2 slope trend). For boundary-dominated flow a 1:1 slope trend occurs at late times. The application of material balance time is particularly useful because this approach provides a constant-rate equivalent for variable flowrate/variable pressure drop data independent of the reservoir properties. (Palacio and Blasingame 1993).
We note a good model match during late times (which is somewhat expected as this behavior is driven by reservoir volume) — however; the match at early times is not particularly good, we believe in most part due to data noise.
For the material balance time period of approximately XXXXX days, the (Dm(p)/qg) "integral" function suggests a 1:2 slope trend, which is indicative of an infinite conductivity vertical fracture. For the material balance time period >xxxx days an approximate 1:1 slope trend is observed, which confirms boundary-dominated flow behavior.
These functions are used for visualizing the behavior of the production data. The analysis is performed by history matching the prescribed reservoir model to the production data functions. .
We adjust the reservoir properties and reservoir volume in order to obtain a model fit. In this case, we chose a vertical well with a single vertical fracture of high conductivity. We find that we were able to achieve a good match of the model against the data trends. This is expected since
Comments:
Material balance time provides a constant-rate equivalent.
(Palacio and Blasingame 1993)
Discussion:
Very good overall model match against data trends.
Boundary-dominated flow is fully developed at 3,000 days MBT.
M.S. Defense | 07 March 2017
Texas A&M University | College Station, TX
Use of Rate Transient Analysis to Evaluate the Well Performance of A Mature Gas Field
Basayir Hussain AL-LAWATI

13. Field Example: Diagnostic "Blasingame" Plot
" Rate Function "
[1:2] Slope
(Linear Flow)
" Rate Integral "
[1:1] Slope
(BDF)
" Rate Integral-Derivative "
Similar to the "Log-Log" plot, the "Blasingame" plot uses (qg/Dm(p)) functions versus Gp/qg as alternate means of presenting and diagnosing data. From the schematic Blasingame plot which uses the rate "integral derivative" function to highlight various flow regimes. For reference, the "Blasingame" plot presents a (negative) unit slope during boundary-dominated flow. Transient flow features observed on the "Blasingame" plot depend on the nature of the prescribed reservoir model(s).
We present the "Blasingame" plot constructed for BHA Well 112 where all of the (qg/Dm(p)) functions are plotted versus Gp/qg. The "Blasingame" plot is somewhat more susceptible to data noise. Although the rate function (qg/Dm(p)) is typically less affected, the integral and integral derivative functions are often significantly affected by data noise. There are schemes to edit spurious data, but such schemes are not used in this work. As shown in Fig. 9, the (qg/Dm(p)) data function (red symbols) is fairly well-behaved, but the auxiliary functions are affected. The model match is actually quite good for the (qg/Dm(p)) function. And as noted, the auxiliary functions could be improved with judicious editing of the (qg/Dm(p)) data function (red symbols). For this work, we use the "Blasingame" plot as a check for the match of the data and model functions, and to validate certain flow regimes (e.g., linear flow and boundary-dominated flow).
A good model match is achieved during late times. Based on these plots, we believe that boundary-dominated flow is fully developed at 3,000 days material balance time.
We note a good model match during late times (which is somewhat expected as this behavior is driven by reservoir volume) — however; the match at early times is not particularly good, we believe in most part due to data noise. Specific to the "Blasingame" plot (Fig. 21), we note considerable instability in the raw productivity index (red circle symbols), which leads to very poor performance of the auxiliary functions (i.e., the "rate integral" function (blue symbols) and the "rate-integral derivative" function (green symbols). Our interpretation from Fig. 20 and Fig. 21 is that boundary-dominated flow is fully developed in at ≈2,000 days material balance time.
3,000 days material balance time
Comments:
More susceptible to noise than the "Log-Log" plot.
Used to validate flow regime, where BDF is observed (>5,000 days).
Uniform flux model used
Little to no dip in pressure between , higher pressure
Good matches on log log and pressure normalized rate of blasingame plot
We use the "diagnostic plots", "Log-Log" plot (Fig. 32) and the "Blasingame" plot (Fig. 33), for RTA to determine different flow regimes. The model fit is obtained by adjusting the reservoir properties and reservoir volume, where for the case of BHA Well 112, we chose a vertical well with a single vertical fracture of high conductivity. A good model match is achieved during late times. Based on these plots, we believe that boundary-dominated flow is fully developed at 800 days material balance time.
Discussion:
Instability in productivity index yields poor character in auxiliary functions.
Auxiliary functions (green/blue symbols) representative for > 200 days MBT.
Boundary-dominated flow is fully developed at 3,000 days MBT.
M.S. Defense | 07 March 2017
Texas A&M University | College Station, TX
Use of Rate Transient Analysis to Evaluate the Well Performance of A Mature Gas Field
Basayir Hussain AL-LAWATI

14. Field Example: Production History Plot - RTA Match
Here we have the traditional "history match" plot of rate, cumulative production, and pressure as functions of time. An excellent model match is achieved. I’d like to mention that as in most cases use of "time-dependent skin" was essential to capturing the behavior exhibited during certain production periods.
A good overall pressure match is achieved until ≈3,700 days, where calculated bottomhole pressures decreased from ≈2,100-1,700 psia after the installation of the first-stage surface compressor. During this period, we note that despite the use of "time-dependent skin", the model suggests that these flowrates should produce a smaller pressure drop than those recorded, resulting in a slight pressure mismatch during this period.
Discussion:
Excellent model match is achieved.
"Time-dependent skin" is used to match several production periods.
M.S. Defense | 07 March 2017
Texas A&M University | College Station, TX
Use of Rate Transient Analysis to Evaluate the Well Performance of A Mature Gas Field
Basayir Hussain AL-LAWATI

15. Field Example: RTA Pressure Extrapolation Scenarios
We used three scenarios to extrapolate the pressure to generate 30-year performance forecasts for the RTA model.
extending from the last known pressure to the assumed abandonment pressure of 200 psia).
RTA Scenario:
Case 1: Constant flowing bottomhole pressure (pwf) — 1,150 psia.
Case 2: pwf reduced yearly — from 1,150 to 200 psia.
Case 3: pwf reduced every 5 years — from 1,150 to 200 psia.
M.S. Defense | 07 March 2017
Texas A&M University | College Station, TX
Use of Rate Transient Analysis to Evaluate the Well Performance of A Mature Gas Field
Basayir Hussain AL-LAWATI

16. Forecast: 30-year Production Forecast Comparison
In this slide we have the 3 rate extrapolations generated from the RTA models and the rate extrapolations generated from the two DCA models (i.e., the modified hyperbolic (MH) and the power-law exponential (PLE)). We note that in this case (BHA Well 112), the RTA predictions are comparable to the DCA extrapolations, with PLE being the most conservative model.
Discussion:
RTA predications are comparable to DCA extrapolations.
PLE is the most conservative model.
M.S. Defense | 07 March 2017
Texas A&M University | College Station, TX
Use of Rate Transient Analysis to Evaluate the Well Performance of A Mature Gas Field
Basayir Hussain AL-LAWATI

17. Field Example: RTA Extrapolation Scenario Comparison
As a final comparison, we present the RTA extrapolations on a semilog "rate-cumulative” and the pressure vs. cumulative production plot. The most aggressive depletion occurs for the constant pwf extrapolation (i.e., pwf = 2600 psia). The other two scenarios show there is a "path-dependency" (as would be expected), but since both scenarios are taken to the abandonment pressure of 200 psia, the total gas recovery for each scenario is the same. We find that by decreasing the intake pressure in the RTA case from a constant 1150 psia to the assumed abandonment pressure of 200 psia predicts a 19 % increase in production.
Discussion:
The most aggressive scenario is shown by case 1.
Path-dependency is observed cases 2 and 3 (but yield same recovery).
Cases 2 and 3 predict 19 percent more total gas recovery than Case 1.
M.S. Defense | 07 March 2017
Texas A&M University | College Station, TX
Use of Rate Transient Analysis to Evaluate the Well Performance of A Mature Gas Field
Basayir Hussain AL-LAWATI

18. 30-Year EUR Correlation Results
Once each well is analyzed, we attempt to correlate the results of the two DCA methods used in this work.…
M.S. Defense | 07 March 2017
Texas A&M University | College Station, TX
Use of Rate Transient Analysis to Evaluate the Well Performance of A Mature Gas Field
Basayir Hussain AL-LAWATI

19. Correlation Plots: DCA Comparison of 30-Year EUR
MH vs. PLE
Here we plot the 30-year EUR for the MH DCA model vs. the EUR for the PLE DCA model. From the perfect correlation trendline, we find that there is less than 4% difference between the EUR results obtained from each of the two relations, with the MH relation having slightly higher EUR, while the PLE tends to be more conservative.
Discussion:
Difference between the two EUR results is less than 4 percent.
The MH relation predicts slightly higher EUR results.
The PLE relation tends to be more conservative.
M.S. Defense | 07 March 2017
Texas A&M University | College Station, TX
Use of Rate Transient Analysis to Evaluate the Well Performance of A Mature Gas Field
Basayir Hussain AL-LAWATI

20. Correlation Plots: RTA Comparison of 30-Year EUR
Case 1 vs. Case 2
Case 1 vs. Case 3
Case 2 vs. Case 3
Here we have 3 correlation plots to compare between the three different pressure extrapolation scenarios used. To remind you.. Case 1 assumes constant intake pressure, in case 2 the flowing bottomhole pressure decreases yearly, and finally in case 3, it decreases every three years. From the slope of the best fit trendline, we find that on average case 2 is ~3% higher than case 1, Cases 1 and 3 are very similar (3 slightly higher), and finally Case 2 is 2.5% higher than case 2.
This difference is dependent on the development plan of the field. Given pwf decreases yearly, in the scenario of case 2, gas production can be accelerated due to path dependency. Cases 2 and 3 will ultimately result in the same cumulative production. Longer time is required for case 3.
Case 2: + 3%
Case 3: + 0.5%
Case 2: + 2.5%
Discussion:
Gas production is accelerated (slightly) in Case 2 (pwf decreases yearly).
M.S. Defense | 07 March 2017
Texas A&M University | College Station, TX
Use of Rate Transient Analysis to Evaluate the Well Performance of A Mature Gas Field
Basayir Hussain AL-LAWATI

21. Correlation Plots: DCA and RTA Comparison of 30-Year EUR
MH vs. RTA case 1
PLE vs. RTA case 1
Next, I’d like to present correlation plots for the 30-year EUR forecast obtained using the DCA methods (PLE and MH) and case 1 of the RTA correlations…. We find that although EUR values are very similar, PLE tends to be slightly more conservative.
We created correlations of EUR results and model parameters for the DCA relations and estimates of reservoir properties obtained from RTA. Parametric correlations developed for the STGIIP, xf, and kh parameters provide a means to attain RTA parameters using DCA relations.
Next, I’d like to present correlation plots for the 30-year EUR forecast obtained using the DCA and case 1 of the RTA correlations…. We find that although EUR values are very similar, PLE tends to be slightly more conservative. In reviewing the EUR from case 1 vs. Case, we note that case 2 predicts slightly higher reserves since this case assumes decreases pwf.
Discussion:
Comparison of DCA EUR results to RTA case 1 (constant pwf).
For low values of EUR, smaller deviations are observed.
In general, EUR deviations increase with higher values of EUR.
M.S. Defense | 07 March 2017
Texas A&M University | College Station, TX
Use of Rate Transient Analysis to Evaluate the Well Performance of A Mature Gas Field
Basayir Hussain AL-LAWATI

22. Parametric Correlation Results
We next correlate the RTA results.
M.S. Defense | 07 March 2017
Texas A&M University | College Station, TX
Use of Rate Transient Analysis to Evaluate the Well Performance of A Mature Gas Field
Basayir Hussain AL-LAWATI

23. Parametric Correlation Work:
RTA Parametric Correlation
DCA and RTA Parametric Correlations
RTA Estimation of:
Gas-in-place
RTA Properties:
kh, xf, pi, s
RTA Estimations of:
Gas-in-place kh xf
DCA Parameters:
MH: b, qi, and Di
2. PLE: 𝒒 𝒊 , 𝑫 𝒊 , n
We attempted to find a parametric relationship to calculate the in place volumes using the well/reservoir parameters obtained from our RTA analysis and inplace volumes estimated from RTA.
We therefore plot the calculated STGIIP versus the STGIIP obtained from RTA and find that a fairly good relationship is achieved between the two. Gas-in-place does not vary for each case since it is not dependent on the development plan of the field.
M.S. Defense | 07 March 2017
Texas A&M University | College Station, TX
Use of Rate Transient Analysis to Evaluate the Well Performance of A Mature Gas Field
Basayir Hussain AL-LAWATI

24. Correlation Plots: STGIIP estimation using RTA well/reservoir properties
We attempted to find a parametric relationship to calculate the in place volumes using the well/reservoir parameters obtained from our RTA analysis and inplace volumes estimated from RTA.
We therefore plot the calculated STGIIP versus the STGIIP obtained from RTA and find that a fairly good relationship is achieved between the two. Gas-in-place does not vary for each case since it is not dependent on the development plan of the field.
Discussion:
Gas-in-place does not vary for each case.
Gas-in-place is not dependent on the development plan of the field.
M.S. Defense | 07 March 2017
Texas A&M University | College Station, TX
Use of Rate Transient Analysis to Evaluate the Well Performance of A Mature Gas Field
Basayir Hussain AL-LAWATI

25. Modified Hyperbolic DCA Relation Power-Law Exponential DCA Relation
Correlation Plots: STGIIP estimation using DCA parameters
Modified Hyperbolic DCA Relation
Power-Law Exponential DCA Relation
COME BACK Ilk et al. (2010) provided a review of the tools available to diagnose and assess a reservoir, the challenges and pitfalls pertinent to production analysis, and guidance for best practices. Due to non-uniqueness in estimating well and reservoir properties using production analysis in unconventional reservoirs, Ilk et al. (2011) suggested the need to couple production analysis with other techniques. They demonstrate a workflow consisting of production data diagnostics, production data analysis, and production forecast to evaluate well performance of a reservoir. Ilk et al. (2011) used parametric correlations to integrate rate-time analysis and model-based production analysis to wells in four fields (shale and tight gas reservoirs). He concluded that formation permeability and fracture half-length are well correlated with parameters of time-rate relations, provided a large number of wells and high quality of data are available.
Discussion:
Excellent correlation between gas-in-place from DCA and RTA.
Gas-in-place for the MH relation correlates extremely well with RTA results.
Gas-in-place for the PLE relation is less well correlated (slightly high DCA).
M.S. Defense | 07 March 2017
Texas A&M University | College Station, TX
Use of Rate Transient Analysis to Evaluate the Well Performance of A Mature Gas Field
Basayir Hussain AL-LAWATI

26. Modified Hyperbolic DCA Relation Power-Law Exponential DCA Relation
Correlation Plots: xf estimation using DCA Parameters
Modified Hyperbolic DCA Relation
Power-Law Exponential DCA Relation
COME BACK We created parametric correlations using for the model parameters for the DCA relations and estimates of reservoir properties obtained from RTA. Parametric correlations developed for the STGIIP, xf, and kh parameters provide a means to attain RTA parameters using DCA relations.
Discussion:
Very good correlation between of fracture half-length with DCA parameters.
Single outlier for fracture half-length correlate with MH DCA parameters.
Single outlier for fracture half-length correlate with PLE DCA parameters.
M.S. Defense | 07 March 2017
Texas A&M University | College Station, TX
Use of Rate Transient Analysis to Evaluate the Well Performance of A Mature Gas Field
Basayir Hussain AL-LAWATI

27. Power-Law Exponential
Correlation Plots: kh estimation using DCA Parameters
Modified Hyperbolic
Power-Law Exponential
COME BACK We created correlations of EUR results and model parameters for the DCA relations and estimates of reservoir properties obtained from RTA. Parametric correlations developed for the STGIIP, xf, and kh parameters provide a means to attain RTA parameters using DCA relations.
Discussion:
Good correlation between of permeability-thickness with DCA parameters.
Single outlier for permeability-thickness correlation — MH DCA parameters.
Permeability-thickness correlates reasonably well for PLE DCA parameters.
M.S. Defense | 07 March 2017
Texas A&M University | College Station, TX
Use of Rate Transient Analysis to Evaluate the Well Performance of A Mature Gas Field
Basayir Hussain AL-LAWATI

28. Conclusions:
The data utilized for the BHA field study (this work) are generally acceptable for reservoir engineering calculations.
The DCA (MH and PLE) relations tend to result in more conservative production estimates (and EUR results) than RTA.
The RTA performed in this work is robust and relevant for all of the cases considered.
The parametric correlations confirm expected relationships of reservoir properties, DCA parameters, and EUR estimates.
The gas-in-place, fracture half-length, and permeability-thickness product estimated using RTA are, in general, highly correlated with the DCA parameters estimated in this work.
This methodology can be used to constrain EUR estimates for other assets.
An advantage of developing parametric correlations is use of these correlations to estimate reservoir properties and in-place volumes without the need to perform RTA on all wells in the field.
To conclude..
We believe that the RTA work performed in this work is robust and relevant for the 14 well cases considered in this work.
M.S. Defense | 07 March 2017
Texas A&M University | College Station, TX
Use of Rate Transient Analysis to Evaluate the Well Performance of A Mature Gas Field
Basayir Hussain AL-LAWATI

29. Analysis of Well Performance Field Example — BHA Well 112
Masters of Science Thesis Defense
March 3, 2017| College Station, TX
Analysis of Well Performance
Field Example — BHA Well 112
End of Presentation
Department of Petroleum Engineering
Texas A&M University
College Station, TX (USA)
Basayir Al-Lawati
I will demonstrate with a field example, BHA Well 112, how each of the 14 wells in this work was analyzed.
M.S. Defense | 07 March 2017
Texas A&M University | College Station, TX
Use of Rate Transient Analysis to Evaluate the Well Performance of A Mature Gas Field
Basayir Hussain AL-LAWATI