**Source**

**SPE Disciplines**

**Geologic Time**

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**Concept Tag**

- al-haddad (1)
- algorithm (1)
- Artificial Intelligence (1)
- bottom-hole pressure (1)
- boundary (1)
- cartesian plot (1)
- Circulation Time (1)
- conventional horner plot (1)
- convolution time (1)
- derivative curve (1)
- dimensionless horner time (1)
- downhole shut-in device (1)
- Drillstem Testing (4)
- drillstem/well testing (4)
- equation (2)
- flow model (1)
- flow period (1)
- formation linear-flow (1)
- formation temperature (1)
- gas lift well (1)
- geothermal reservoir (1)
- Horner plot (1)
- interpretation (2)
- Laplace space (1)
- machine learning (1)
- model parameter (1)
- numerical inversion (1)
- objective function (1)
- optimization process (1)
- parameter gradient (1)
- permeability (2)
- pore pressure (1)
- power-law behavior (1)
- pressure data (1)
- pressure derivative data (1)
- pressure transient analysis (1)
- pressure transient testing (1)
- production control (1)
- production logging (1)
- production monitoring (1)
- production rate (1)
- production stage 1 (1)
- rate transient analysis (1)
- reservoir (1)
- Reservoir Surveillance (1)
- reservoir temperature (1)
**shut-in data (4)**- shut-in device (1)
- shut-in period (2)
- shut-in time (1)
- spe 21144 (1)
- spe 39969 (1)
- square root (1)
- static temperature (1)
- storage duration (1)
- straight line (2)
- superposition plot (1)
- surface pressure (1)
- surface shut-in (1)
- temperature buildup (1)
- time plot (1)
- transient temperature data (1)
- true reservoir temperature (1)
- Upstream Oil & Gas (4)
- uta superposition plot (1)
- wellbore (2)
- wellbore pressure (1)
- wellbore storage (1)
- wellbore storage coefficient (1)

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Abstract Market-induced production shut-downs and restarts offer us an opportunity to gather step-rate and shut-in data for pressure transient analysis (PTA) and rate transient analysis (RTA). In this study, we present a unified transient analysis (UTA) to combine PTA and RTA in a single framework. In this new approach continuous production data, step-rate data, shut-in data and re-start data can be visualized and analyzed in a single superposition plot, which can be used to estimate both and infer formation pore pressure in a holistic manner by utilizing all available data. Most importantly, we show that traditional log-log and square root of time plots can lead to false interpretation of the termination of linear-flow or power-law behavior. Field cases are presented to demonstrate the superiority of the newly introduced superposition plot, along with discussion on the calibration of long-term bottom-hole pressure with short-term measurements.

bottom-hole pressure, cartesian plot, convolution time, Drillstem Testing, drillstem/well testing, formation linear-flow, pore pressure, power-law behavior, pressure transient analysis, pressure transient testing, production rate, production stage 1, rate transient analysis, reservoir, shut-in data, square root, straight line, superposition plot, surface pressure, time plot, Upstream Oil & Gas, uta superposition plot

Oilfield Places:

- North America > United States > Texas > Permian Basin (0.98)
- North America > United States > New Mexico > Permian Basin (0.98)

SPE Disciplines:

Abstract The main source for formation damage measurement is transient well testing. The formation damage measured is referred to as the skin factor. To reduce cost and operational risk, many wells are tested with surface shut-in and bottomhole pressure measurement. If properly designed, performed, and interpreted, these tests provide valuable information on the well's skin condition. Wellbore storage becomes a very important factor with a surface shut-in. In addition to the wellbore fluids' compression and phase changes, temperature effects may be significant and extended depending on many factors including the well's depth. However, field data has shown that available analytical models do not accurately predict wellbore storage duration and pressure behavior. Moreover, extended wellbore storage pressure data may appear to behave in a way similar to radial flow as seen on the pressure derivative curve. This misinterpretation usually results in a negative skin and the creation of nearby boundaries (i.e. which results in smaller reservoirs) making high potential wells appear to be limited. This paper will present empirical and practical field solutions to this problem. Well test, stimulation, and production field data supported by computer simulations from oil and gas wells in the Gulf of Mexico area will be presented. The data presented in this paper will demonstrate how the test design and interpretation will effect the overall reservoir and well management of the field. P. 119

al-haddad, boundary, derivative curve, downhole shut-in device, Drillstem Testing, drillstem/well testing, formation temperature, gas lift well, interpretation, permeability, pressure derivative data, shut-in data, shut-in device, shut-in period, spe 39969, storage duration, surface shut-in, Upstream Oil & Gas, wellbore, wellbore storage

SPE Disciplines: Reservoir Description and Dynamics > Formation Evaluation & Management > Drillstem/well testing (1.00)

Abstract

This paper describes a method for automated interpretation of drillstemtests (DST's) for the cases in which the produced fluids do not fill up thedrillstring. The method is based upon the pressure matching of field data witha theoretical fluid flow model through the use of an unconstrained non-linearregression technique, coupled with numerical inversion of Laplace transforms ofthe wellbore pressure for both flowing and shutin periods. The parametergradients required to implement the fitting process have also been obtained bynumerically inverting closed form expressions from Laplace space. A DST hasbeen treated as a "slug test" with a step change in the wellborestorage coefficient at shut-in time. With this concept it has been possible tointerpret flow and shut-in pressure data simultaneously. Both simulated andfield pressure data have been analyzed in order to illustrate the applicationof the method using a fluid flow model which considers a homogeneous andinfinite reservoir system, including wellbore storage and skin effects.Application of the method presented in this work to field data may yieldestimates of reservoir and wellbore parameters such as the formationpermeability, the skin parameters such as the formation permeability, the skineffect and the initial reservoir pressure. Such parameters are important to thedetermination of wellbore condition and to the forecast of hydrocarbonproduction. The methodology described in this paper may be used to extend theautomated data fitting algorithm to `include more complex fluid flow models,such as fractured or composite systems and other flow geometries.

Introduction

Interpretation of drillstem test pressure measurements have been usuallyperformed by means of either type-curve matching or specialized plots ofpressure-time data. When the production period is small, only data from theshut-in period may be properly analyzed. However, in most cases flowing andshut-in pressure data have been analyzed isolately, as in two different tests.According to Correa , a DST may be viewed as a slug test with a step change inwellbore storage. Correa and Ramey have given an analytical solution to the DSTproblem using the concept of a time-dependent boundary problem using theconcept of a time-dependent boundary condition. They have solved thediffusivity equation with a single inner boundary condition, which includedproduction and shut-in effects. Therefore, their solution production andshut-in effects. Therefore, their solution can be used to analyze the overallDST history as a single process. This may be effectively achieved by means ofprocess. This may be effectively achieved by means of a non-linear regressiontechnique by fitting the pressure response of a theoretical flow model to dataof both flow and shut-in phases. Rosa and Horne have described an automatedtype-curve matching process using parameter gradients computed from numericalin version of analytical equations in Laplace space. Barua and Horne havecompared the performance of some regression analysis algorithms, concludingthat if there is only one ill defined parameter the Levenberg and Marquadtalgorithm gives the best results. This work describes a technique to provideestimates of the reservoir parameters and wellbore condition, by means of anautomated analysis of a DST pressure history. pressure history.

algorithm, Artificial Intelligence, Drillstem Testing, drillstem/well testing, equation, flow model, flow period, interpretation, Laplace space, machine learning, model parameter, numerical inversion, objective function, optimization process, parameter gradient, permeability, pressure data, shut-in data, shut-in period, spe 21144, Upstream Oil & Gas, wellbore pressure, wellbore storage coefficient

SPE Disciplines: Reservoir Description and Dynamics > Formation Evaluation & Management > Drillstem/well testing (1.00)

Technology: Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning > Regression (0.90)

Abstract

In order to develop good estimates on the heat content of a geothermal reservoir and its formation resistivities, and for various drilling and completion decisions one needs, an accurate estimate of the formation temperature. Previous methods to determine static temperature required long shut in periods. The static temperature obtained using the conventional Horner plots were lower than the true reservoir temperature. A quick and easy method has been developed to calculate static temperature from early shut in data in geothermal wells, This method determines static temperature values which are closer to the true reservoir temperature than those obtained from the conventional Horner plot. Recommendation for recording pertinent data to be used in the analysis of temperature buildup and determining initial reservoir temperatures are provided. Several examples are also given.

Introduction

To evaluate geothermal reservoirs, the static formation temperature needs to be established as accurately as possible. A knowledge of the true, static formation temperature is required in estimating the heat content of geothermal reservoirs. The interpretation of electric logs requires accurate formation resistivities, which are dependent on temperature. Reliable static temperature is important in designing completion programs and establishing geothermal gradients. programs and establishing geothermal gradients.

However, the temperatures recorded during logging operations are usually lower than the static temperature. These low temperatures are caused by the cooling effect of the mud during circulation. As soon as circulation stops, the temperature around the wellbore begins to increase. Complete temperature recovery in a new well may take anywhere from a few hours to a few months, depending on the formation, well characteristics, and the mud circulating time. A long wait for complete temperature recovery could cause a sizeable increase in drilling costs; hence a less time consuming method is needed to calculate static temperature using early shut-in data.

The common practice in the geothermal industry is to use Horner plots for estimating static reservoir temperature from temperature buildup data. The buildup temperature is plotted against the logarithm of dimensionless Horner time, (tp + t)/ t, where tp is the circulation time before shut-in and t is the buildup time. The data points are then fitted to a straight line, which is extrapolated to an infinite t, i.e., a dimensionless Horner time of unity. The corresponding extrapolated temperature is taken as the true reservoir temperature. This method is based on the "line source solution" to the diffusivity equation which describes the radial conductive heat flow in an infinite system with a verical line sink withdrawing heat at a constant rate. Unfortunately, the conventional Horner plot approach yields values of apparent static temperature which is lower than the true reservoir temperature.

Circulation Time, conventional horner plot, dimensionless horner time, Drillstem Testing, drillstem/well testing, equation, geothermal reservoir, Horner plot, production control, production logging, production monitoring, Reservoir Surveillance, reservoir temperature, shut-in data, shut-in time, static temperature, straight line, temperature buildup, transient temperature data, true reservoir temperature, Upstream Oil & Gas, wellbore

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